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README.md ADDED
@@ -0,0 +1,44 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Note: This recipe is trained with the codes from this PR https://github.com/k2-fsa/icefall/pull/428
2
+ # Pre-trained Transducer-Stateless5 models for the TAL_CSASR dataset with icefall.
3
+ The model was trained on the far data of [TAL_CSASR](https://ai.100tal.com/dataset) with the scripts in [icefall](https://github.com/k2-fsa/icefall) based on the latest version k2.
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+ ## Training procedure
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+ The main repositories are list below, we will update the training and decoding scripts with the update of version.
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+ k2: https://github.com/k2-fsa/k2
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+ icefall: https://github.com/k2-fsa/icefall
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+ lhotse: https://github.com/lhotse-speech/lhotse
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+ * Install k2 and lhotse, k2 installation guide refers to https://k2.readthedocs.io/en/latest/installation/index.html, lhotse refers to https://lhotse.readthedocs.io/en/latest/getting-started.html#installation. I think the latest version would be ok. And please also install the requirements listed in icefall.
10
+ * Clone icefall(https://github.com/k2-fsa/icefall) and check to the commit showed above.
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+ ```
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+ git clone https://github.com/k2-fsa/icefall
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+ cd icefall
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+ ```
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+ * Preparing data.
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+ ```
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+ cd egs/tal_csasr/ASR
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+ bash ./prepare.sh
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+ ```
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+ * Training
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+ ```
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+ export CUDA_VISIBLE_DEVICES="0,1,2,3,4,5"
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+ ./pruned_transducer_stateless5/train.py \
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+ --world-size 6 \
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+ --num-epochs 30 \
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+ --start-epoch 1 \
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+ --exp-dir pruned_transducer_stateless5/exp \
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+ --lang-dir data/lang_char \
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+ --max-duration 90
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+ ```
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+ ## Evaluation results
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+ The decoding results (CER%) on TAL_CSASR(dev and test) are listed below:
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+
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+ |decoding-method | epoch(iter) | avg | dev | test |
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+ |--|--|--|--|--|
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+ |greedy_search | 30 | 24 | 7.49 | 7.58|
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+ |modified_beam_search | 30 | 24 | 7.33 | 7.38|
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+ |fast_beam_search | 30 | 24 | 7.32 | 7.42|
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+ |greedy_search(use-averaged-model=True) | 30 | 24 | 7.30 | 7.39|
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+ |modified_beam_search(use-averaged-model=True) | 30 | 24 | 7.15 | 7.22|
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+ |fast_beam_search(use-averaged-model=True) | 30 | 24 | 7.18 | 7.26|
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+ |greedy_search | 348000 | 30 | 7.46 | 7.54|
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+ |modified_beam_search | 348000 | 30 | 7.24 | 7.36|
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+ |fast_beam_search | 348000 | 30 | 7.25 | 7.39 |
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+ size 3157223
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+ size 325654
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88
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89
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90
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91
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92
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93
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94
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95
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96
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97
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98
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99
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100
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101
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102
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103
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113
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116
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117
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118
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119
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121
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122
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123
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124
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125
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127
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128
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129
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133
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134
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135
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136
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137
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138
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142
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143
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144
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146
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147
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148
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149
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150
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151
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152
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153
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154
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155
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156
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157
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158
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159
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160
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161
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162
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163
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164
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165
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166
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167
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168
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169
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170
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171
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172
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173
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174
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175
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176
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177
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178
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179
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180
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181
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182
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183
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184
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185
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186
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187
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188
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189
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190
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191
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192
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193
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194
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195
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196
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197
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198
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199
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200
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201
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202
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203
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204
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205
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206
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207
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208
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209
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210
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211
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212
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213
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214
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215
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216
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217
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218
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219
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220
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221
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222
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223
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224
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225
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226
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227
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228
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229
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230
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231
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232
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233
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234
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235
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236
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237
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238
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239
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240
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241
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242
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243
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244
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245
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246
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247
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248
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249
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250
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251
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252
+ ▁M 251
253
+ ▁B 252
254
+ ▁E 253
255
+ 等 254
256
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257
+ ▁N 256
258
+ 把 257
259
+ 分 258
260
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261
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262
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263
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264
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265
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266
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267
+ ▁AT 266
268
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269
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270
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271
+ ▁I 270
272
+ M 271
273
+ ▁GOING 272
274
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275
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276
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277
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278
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279
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280
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281
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282
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283
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284
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285
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286
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287
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288
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289
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290
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291
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292
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293
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294
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295
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296
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297
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298
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299
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300
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301
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302
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303
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304
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305
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306
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307
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308
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309
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310
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311
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312
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313
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314
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315
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316
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317
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318
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319
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320
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321
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322
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323
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324
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325
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326
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327
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328
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329
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330
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331
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332
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333
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334
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335
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336
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337
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338
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339
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340
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341
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342
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343
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344
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345
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346
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347
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348
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349
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350
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351
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352
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353
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354
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355
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356
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357
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358
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359
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360
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361
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362
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363
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364
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365
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366
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367
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368
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369
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370
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371
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372
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373
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374
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375
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376
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377
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378
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379
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380
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381
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382
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383
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384
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385
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386
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387
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388
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389
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390
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391
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392
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393
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394
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395
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396
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397
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398
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399
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400
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401
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402
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403
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404
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405
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406
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407
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408
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409
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410
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411
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412
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413
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414
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415
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416
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417
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418
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419
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420
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421
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422
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423
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424
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425
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426
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427
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428
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429
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430
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431
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432
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433
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434
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435
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436
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437
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438
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439
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440
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441
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442
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443
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444
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445
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446
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447
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448
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449
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450
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451
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452
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453
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454
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455
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456
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457
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458
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459
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460
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461
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462
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463
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464
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465
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466
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467
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468
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469
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470
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471
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472
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473
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474
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475
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476
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477
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478
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479
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480
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481
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482
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483
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484
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485
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486
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487
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488
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489
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490
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491
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492
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493
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494
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495
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496
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497
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498
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499
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500
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501
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502
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503
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504
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505
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506
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507
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508
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509
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510
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511
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512
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513
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514
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515
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516
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517
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518
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519
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520
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521
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522
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523
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524
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525
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526
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527
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528
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529
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530
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531
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532
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533
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534
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535
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536
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537
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538
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539
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540
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541
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542
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543
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544
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545
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546
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547
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548
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549
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550
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551
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552
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553
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554
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555
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556
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557
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558
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559
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560
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562
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563
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564
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565
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566
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567
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568
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569
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570
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571
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572
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573
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574
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575
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576
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577
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578
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579
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580
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581
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582
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583
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584
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585
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586
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587
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588
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589
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590
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591
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592
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593
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594
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595
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596
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597
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598
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599
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600
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601
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602
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603
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604
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605
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606
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607
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608
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609
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610
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611
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612
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613
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614
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615
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616
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617
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618
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619
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620
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621
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622
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623
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624
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625
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626
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627
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628
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629
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630
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631
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632
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633
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634
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635
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636
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637
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638
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639
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640
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641
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642
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643
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644
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645
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646
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647
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648
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649
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650
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651
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652
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653
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654
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655
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656
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657
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658
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659
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660
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661
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662
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663
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664
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665
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666
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667
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668
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669
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670
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671
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672
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673
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674
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675
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676
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677
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678
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679
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680
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681
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682
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683
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684
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685
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686
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687
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688
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689
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690
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691
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692
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693
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694
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695
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696
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697
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698
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699
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700
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701
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702
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703
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704
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705
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706
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707
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708
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709
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710
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711
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712
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713
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714
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715
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716
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717
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718
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719
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720
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721
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722
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723
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724
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725
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726
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727
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728
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729
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730
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731
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732
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733
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734
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735
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736
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737
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738
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739
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740
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741
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742
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743
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744
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745
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746
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747
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748
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749
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750
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751
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752
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753
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754
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755
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756
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757
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758
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759
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760
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761
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762
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763
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764
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765
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766
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767
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768
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769
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770
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771
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772
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773
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774
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775
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776
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777
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778
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779
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780
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781
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782
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783
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784
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785
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786
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787
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788
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789
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790
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791
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792
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793
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794
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795
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796
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797
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798
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799
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800
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801
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802
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803
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804
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805
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806
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807
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808
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809
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810
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811
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812
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813
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814
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815
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816
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817
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818
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819
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820
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821
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822
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823
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824
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825
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826
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827
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828
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829
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830
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831
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832
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833
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834
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835
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836
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837
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838
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839
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840
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841
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842
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843
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844
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845
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846
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847
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848
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849
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850
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851
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852
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853
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854
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855
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856
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857
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858
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859
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860
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861
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862
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863
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864
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865
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866
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867
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868
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869
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870
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871
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872
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873
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874
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875
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876
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877
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+ 店 1549
1551
+ ▁WRIT 1550
1552
+ TING 1551
1553
+ ▁GLAD 1552
1554
+ ▁HEAR 1553
1555
+ 剩 1554
1556
+ ▁DOCTOR 1555
1557
+ ▁EXERCISE 1556
1558
+ DO 1557
1559
+ ▁QUARTER 1558
1560
+ ▁WENT 1559
1561
+ INE 1560
1562
+ MA 1561
1563
+ 院 1562
1564
+ ▁ONCE 1563
1565
+ ▁WEEK 1564
1566
+ ▁SEEM 1565
1567
+ 千 1566
1568
+ 万 1567
1569
+ 百 1568
1570
+ ▁HUNDRED 1569
1571
+ 漏 1570
1572
+ 汇 1571
1573
+ 扮 1572
1574
+ 演 1573
1575
+ 符 1574
1576
+ ▁OCTOBER 1575
1577
+ 技 1576
1578
+ 巧 1577
1579
+ 叹 1578
1580
+ 羊 1579
1581
+ ▁CHICKEN 1580
1582
+ ENT 1581
1583
+ 挑 1582
1584
+ 煮 1583
1585
+ ▁SUN 1584
1586
+ ▁SHINE 1585
1587
+ ▁SUNSHINE 1586
1588
+ 拉 1587
1589
+ 钩 1588
1590
+ 妈 1589
1591
+ 截 1590
1592
+ ▁SHOUT 1591
1593
+ 湖 1592
1594
+ 泊 1593
1595
+ ▁RIVER 1594
1596
+ ▁MOUNTAIN 1595
1597
+ 美 1596
1598
+ ▁PRE 1597
1599
+ G 1598
1600
+ ANT 1599
1601
+ 怀 1600
1602
+ 孕 1601
1603
+ 轿 1602
1604
+ ▁PARIS 1603
1605
+ 巴 1604
1606
+ 黎 1605
1607
+ 啧 1606
1608
+ 窍 1607
1609
+ 转 1608
1610
+ 折 1609
1611
+ ▁BEAUTY 1610
1612
+ 冒 1611
1613
+ ▁GETT 1612
1614
+ ▁OTHER 1613
1615
+ 鲁 1614
1616
+ 卸 1615
1617
+ ▁ATTITUDE 1616
1618
+ ▁TOWARD 1617
1619
+ ▁WILLING 1618
1620
+ 愿 1619
1621
+ ▁QUITE 1620
1622
+ ▁GUESS 1621
1623
+ 幅 1622
1624
+ ▁LESS 1623
1625
+ 痛 1624
1626
+ 胃 1625
1627
+ 纠 1626
1628
+ 辛 1627
1629
+ 苦 1628
1630
+ 收 1629
1631
+ 获 1630
1632
+ 替 1631
1633
+ 防 1632
1634
+ 枪 1633
1635
+ 摩 1634
1636
+ 氢 1635
1637
+ 氧 1636
1638
+ 钡 1637
1639
+ 战 1638
1640
+ 违 1639
1641
+ ▁FE 1640
1642
+ ▁RISK 1641
1643
+ 险 1642
1644
+ 振 1643
1645
+ ▁OWNER 1644
1646
+ 领 1645
1647
+ ▁PARTNER 1646
1648
+ 伸 1647
1649
+ ▁SIGHT 1648
1650
+ ▁SEE 1649
1651
+ ▁ARTICLE 1650
1652
+ ▁EXCEPT 1651
1653
+ ▁TOO 1652
1654
+ 跳 1653
1655
+ 睡 1654
1656
+ 借 1655
1657
+ 环 1656
1658
+ 肩 1657
1659
+ 膀 1658
1660
+ 坐 1659
1661
+ ▁PROTECT 1660
1662
+ ION 1661
1663
+ 充 1662
1664
+ 悦 1663
1665
+ ▁PAIN 1664
1666
+ 疼 1665
1667
+ 麻 1666
1668
+ 木 1667
1669
+ 狡 1668
1670
+ 猾 1669
1671
+ 懒 1670
1672
+ 惰 1671
1673
+ 私 1672
1674
+ 占 1673
1675
+ 宜 1674
1676
+ 甘 1675
1677
+ 堕 1676
1678
+ IF 1677
1679
+ 呵 1678
1680
+ 卡 1679
1681
+ 模 1680
1682
+ 肖 1681
1683
+ 输 1682
1684
+ ▁BECAUSE 1683
1685
+ 健 1684
1686
+ 康 1685
1687
+ 增 1686
1688
+ ME 1687
1689
+ ▁WONDERFUL 1688
1690
+ 妙 1689
1691
+ ▁WONDER 1690
1692
+ ▁CENTER 1691
1693
+ ▁USED 1692
1694
+ ▁FACTOR 1693
1695
+ ▁IMAGINE 1694
1696
+ ▁CENT 1695
1697
+ 冷 1696
1698
+ ▁J 1697
1699
+ 属 1698
1700
+ ▁SUCCESSFUL 1699
1701
+ ▁SUCCESS 1700
1702
+ 贴 1701
1703
+ ▁REALLY 1702
1704
+ ▁EXC 1703
1705
+ RI 1704
1706
+ ENCE 1705
1707
+ 历 1706
1708
+ 丽 1707
1709
+ 田 1708
1710
+ 幸 1709
1711
+ 担 1710
1712
+ 忧 1711
1713
+ ▁HARD 1712
1714
+ 弧 1713
1715
+ 阴 1714
1716
+ ▁POL 1715
1717
+ IT 1716
1718
+ IC 1717
1719
+ ▁PO 1718
1720
+ ▁LI 1719
1721
+ ▁TI 1720
1722
+ C 1721
1723
+ 免 1722
1724
+ 证 1723
1725
+ 播 1724
1726
+ 质 1725
1727
+ 戒 1726
1728
+ ▁ST 1727
1729
+ ANCE 1728
1730
+ 逆 1729
1731
+ 誓 1730
1732
+ 唔 1731
1733
+ ▁PART 1732
1734
+ ▁HAPPENED 1733
1735
+ ▁TH 1734
1736
+ IE 1735
1737
+ 喽 1736
1738
+ 恰 1737
1739
+ 硫 1738
1740
+ 酸 1739
1741
+ 淀 1740
1742
+ 初 1741
1743
+ ▁CHOICE 1742
1744
+ 论 1743
1745
+ ▁MEETING 1744
1746
+ ▁AUTUMN 1745
1747
+ 核 1746
1748
+ 惑 1747
1749
+ ▁HOWEVER 1748
1750
+ 尽 1749
1751
+ 航 1750
1752
+ ▁TALL 1751
1753
+ 劝 1752
1754
+ 责 1753
1755
+ 务 1754
1756
+ 闻 1755
1757
+ ▁BACK 1756
1758
+ 拜 1757
1759
+ 荣 1758
1760
+ 员 1759
1761
+ ▁FORCE 1760
1762
+ 迫 1761
1763
+ ▁RECALL 1762
1764
+ 倾 1763
1765
+ ▁INTENTION 1764
1766
+ 洞 1765
1767
+ ▁POSSIBLE 1766
1768
+ ▁SOMEONE 1767
1769
+ 飞 1768
1770
+ ▁DRAW 1769
1771
+ ▁ATTENTION 1770
1772
+ ▁WINDOW 1771
1773
+ 鄙 1772
1774
+ 野 1773
1775
+ ▁BUSY 1774
1776
+ DY 1775
1777
+ 冬 1776
1778
+ 装 1777
1779
+ ▁CUSTOM 1778
1780
+ 灯 1779
1781
+ ▁WHY 1780
1782
+ 品 1781
1783
+ ▁THAN 1782
1784
+ ▁CAREFUL 1783
1785
+ 送 1784
1786
+ ▁KINDNESS 1785
1787
+ ▁APPRECIATE 1786
1788
+ ▁THANK 1787
1789
+ ▁FEW 1788
1790
+ ▁UNDERSTAND 1789
1791
+ 效 1790
1792
+ 胜 1791
1793
+ 筹 1792
1794
+ 立 1793
1795
+ ▁YOUNG 1794
1796
+ UL 1795
1797
+ 姐 1796
1798
+ 宁 1797
1799
+ 恩 1798
1800
+ 敲 1799
1801
+ ▁ALSO 1800
1802
+ ▁BELONG 1801
1803
+ ▁LE 1802
1804
+ ▁FORGET 1803
1805
+ ▁RAISE 1804
1806
+ ▁EARLY 1805
1807
+ 墨 1806
1808
+ 镜 1807
1809
+ 社 1808
1810
+ ▁RAPID 1809
1811
+ ▁DEVELOPMENT 1810
1812
+ ▁SOCIETY 1811
1813
+ 尤 1812
1814
+ ▁CHEER 1813
1815
+ ▁RACE 1814
1816
+ ▁BEGAN 1815
1817
+ J 1816
1818
+ MMY 1817
1819
+ ▁STOOD 1818
1820
+ ▁FATHER 1819
1821
+ RA 1820
1822
+ ▁DOWN 1821
1823
+ ▁WHILE 1822
1824
+ DICTION 1823
1825
+ ARY 1824
1826
+ 坏 1825
1827
+ 怕 1826
1828
+ 聊 1827
1829
+ 款 1828
1830
+ ▁DREAM 1829
1831
+ ▁POT 1830
1832
+ 僵 1831
1833
+ 硬 1832
1834
+ 堂 1833
1835
+ ▁BREAD 1834
1836
+ UB 1835
1837
+ BORN 1836
1838
+ ▁REMEMBER 1837
1839
+ ▁FRIENDS 1838
1840
+ ▁COLOR 1839
1841
+ ▁DISLIKE 1840
1842
+ ▁RESPONSIBILIT 1841
1843
+ ▁HOPE 1842
1844
+ ▁CHILDREN 1843
1845
+ ▁DAY 1844
1846
+ 旨 1845
1847
+ ▁PAST 1846
1848
+ ▁SEVEN 1847
1849
+ ▁INSTEAD 1848
1850
+ 锰 1849
1851
+ ▁DRINK 1850
1852
+ ▁TEA 1851
1853
+ 谎 1852
1854
+ ▁KIND 1853
1855
+ ▁HEART 1854
1856
+ ▁VALUE 1855
1857
+ 价 1856
1858
+ ▁TREE 1857
1859
+ ▁PROFESSOR 1858
1860
+ ▁WISH 1859
1861
+ 迟 1860
1862
+ ▁PROGRESS 1861
1863
+ ▁MIGHT 1862
1864
+ 官 1863
1865
+ 钦 1864
1866
+ 佩 1865
1867
+ 羡 1866
1868
+ 慕 1867
1869
+ ▁TILL 1868
1870
+ ▁KNOWLEDGE 1869
1871
+ ▁ABILITY 1870
1872
+ ▁EXPERIENCE 1871
1873
+ ▁MA 1872
1874
+ ▁JOY 1873
1875
+ 杈 1874
1876
+ 震 1875
1877
+ 络 1876
1878
+ 纤 1877
1879
+ 摁 1878
1880
+ 钮 1879
1881
+ ▁SE 1880
1882
+ PT 1881
1883
+ EMBER 1882
1884
+ ▁SHOE 1883
1885
+ ▁TOOK 1884
1886
+ ▁TAKEN 1885
1887
+ ▁WRITE 1886
1888
+ 脚 1887
1889
+ 牙 1888
1890
+ 齿 1889
1891
+ 团 1890
1892
+ 队 1891
1893
+ 袖 1892
1894
+ 滨 1893
1895
+ 吵 1894
1896
+ 闹 1895
1897
+ ▁NONE 1896
1898
+ ▁PRESENCE 1897
1899
+ ▁ANIMALS 1898
1900
+ 耽 1899
1901
+ 兮 1900
1902
+ 陷 1901
1903
+ 莞 1902
1904
+ 请 1903
1905
+ ▁LOVING 1904
1906
+ AU 1905
1907
+ 职 1906
1908
+ 赚 1907
1909
+ 民 1908
1910
+ 币 1909
1911
+ 运 1910
1912
+ ▁JOHN 1911
1913
+ 约 1912
1914
+ 翰 1913
1915
+ 留 1914
1916
+ ▁MOMENT 1915
1917
+ ▁AGO 1916
1918
+ ▁SUIT 1917
1919
+ ABLE 1918
1920
+ 弱 1919
1921
+ ▁PIN 1920
1922
+ ▁PROMISE 1921
1923
+ 惋 1922
1924
+ 惜 1923
1925
+ ▁LIVING 1924
1926
+ ▁ABROAD 1925
1927
+ ▁SEND 1926
1928
+ ▁ET 1927
1929
+ ▁MEN 1928
1930
+ 功 1929
1931
+ 承 1930
1932
+ ▁SUCCEED 1931
1933
+ ▁SHOW 1932
1934
+ 临 1933
1935
+ ▁ANYTHING 1934
1936
+ ▁COUNTRY 1935
1937
+ ▁ASK 1936
1938
+ 启 1937
1939
+ 潜 1938
1940
+ 移 1939
1941
+ ▁STRANGE 1940
1942
+ ▁TRO 1941
1943
+ US 1942
1944
+ 嘴 1943
1945
+ ▁FIND 1944
1946
+ ▁ALLOW 1945
1947
+ 允 1946
1948
+ ▁RAIN 1947
1949
+ ▁DOUBLE 1948
1950
+ ▁COMMUNICAT 1949
1951
+ ▁BELIEVE 1950
1952
+ 碰 1951
1953
+ 搞 1952
1954
+ ▁NUMBER 1953
1955
+ 丈 1954
1956
+ ▁HUSBAND 1955
1957
+ ▁FREE 1956
1958
+ ZE 1957
1959
+ ▁JACK 1958
1960
+ ▁SCENE 1959
1961
+ RY 1960
1962
+ ▁SEEMS 1961
1963
+ ▁HIDE 1962
1964
+ 躲 1963
1965
+ 避 1964
1966
+ ▁CA 1965
1967
+ AGE 1966
1968
+ TY 1967
1969
+ 洋 1968
1970
+ Z 1969
1971
+ ANG 1970
1972
+ ▁GAVE 1971
1973
+ ▁PRESENT 1972
1974
+ ▁SEEN 1973
1975
+ 妇 1974
1976
+ 姓 1975
1977
+ 殷 1976
1978
+ 敬 1977
1979
+ ▁WHITE 1978
1980
+ 莱 1979
1981
+ 克 1980
1982
+ ▁ISRAEL 1981
1983
+ ▁IMPROV 1982
1984
+ ▁AUTOMATIC 1983
1985
+ TIC 1984
1986
+ 舞 1985
1987
+ 阿 1986
1988
+ 姨 1987
1989
+ 丰 1988
1990
+ ▁MOUTH 1989
1991
+ ▁CONCERT 1990
1992
+ BY 1991
1993
+ ▁GA 1992
1994
+ ▁CAUSE 1993
1995
+ AND 1994
1996
+ ▁INTO 1995
1997
+ 若 1996
1998
+ ▁PAR 1997
1999
+ 嘉 1998
2000
+ 盛 1999
2001
+ ▁BEST 2000
2002
+ ▁TITLE 2001
2003
+ ▁SUB 2002
2004
+ WAY 2003
2005
+ ▁CONTROL 2004
2006
+ 控 2005
2007
+ ▁PUSH 2006
2008
+ ▁MOST 2007
2009
+ ▁VISIT 2008
2010
+ ▁COLLEGE 2009
2011
+ 精 2010
2012
+ 牢 2011
2013
+ ▁DIVIDED 2012
2014
+ 贝 2013
2015
+ ▁ACROSS 2014
2016
+ ▁SEA 2015
2017
+ 抽 2016
2018
+ 份 2017
2019
+ ▁EXPRESS 2018
2020
+ 坨 2019
2021
+ ▁ER 2020
2022
+ 矾 2021
2023
+ IUM 2022
2024
+ ▁HATE 2023
2025
+ 域 2024
2026
+ PA 2025
2027
+ 政 2026
2028
+ 党 2027
2029
+ 爸 2028
2030
+ ▁CHEAP 2029
2031
+ ▁WORKING 2030
2032
+ ▁YA 2031
2033
+ LE 2032
2034
+ 耶 2033
2035
+ ▁HERSELF 2034
2036
+ 休 2035
2037
+ 册 2036
2038
+ 征 2037
2039
+ 砍 2038
2040
+ 伐 2039
2041
+ ▁CUT 2040
2042
+ ▁LINE 2041
2043
+ 插 2042
2044
+ 抵 2043
2045
+ 绩 2044
2046
+ ▁TURNED 2045
2047
+ ▁OUGHT 2046
2048
+ ▁MUST 2047
2049
+ ▁VEHICLE 2048
2050
+ ▁HOUR 2049
2051
+ ▁AROUND 2050
2052
+ 屏 2051
2053
+ ▁BROAD 2052
2054
+ 珠 2053
2055
+ 穆 2054
2056
+ 朗 2055
2057
+ 玛 2056
2058
+ ▁HOTEL 2057
2059
+ ▁SET 2058
2060
+ 偿 2059
2061
+ 捐 2060
2062
+ 洗 2061
2063
+ 澡 2062
2064
+ 洒 2063
2065
+ 台 2064
2066
+ 阶 2065
2067
+ 贸 2066
2068
+ ▁SAME 2067
2069
+ 颈 2068
2070
+ 鹿 2069
2071
+ ▁INSTRUMENT 2070
2072
+ ▁DIDN 2071
2073
+ ▁FEEL 2072
2074
+ ▁FACE 2073
2075
+ 噢 2074
2076
+ ▁CRIS 2075
2077
+ 危 2076
2078
+ 攻 2077
2079
+ 守 2078
2080
+ 族 2079
2081
+ 屈 2080
2082
+ 挠 2081
2083
+ 抗 2082
2084
+ OS 2083
2085
+ 沟 2084
2086
+ ▁DESCRIBE 2085
2087
+ ▁HAND 2086
2088
+ IGHT 2087
2089
+ 艾 2088
2090
+ 瑞 2089
2091
+ 曾 2090
2092
+ 尼 2091
2093
+ 迪 2092
2094
+ 残 2093
2095
+ 疾 2094
2096
+ 育 2095
2097
+ 米 2096
2098
+ ▁MET 2097
2099
+ ▁ENOUGH 2098
2100
+ 渣 2099
2101
+ 拾 2100
2102
+ ▁SA 2101
2103
+ ▁FAM 2102
2104
+ OUS 2103
2105
+ ▁BRING 2104
2106
+ ▁ESPECIALLY 2105
2107
+ IAN 2106
2108
+ ▁DISCUSS 2107
2109
+ 扩 2108
2110
+ 咦 2109
2111
+ 亲 2110
2112
+ ▁CITIES 2111
2113
+ ▁THESE 2112
2114
+ ▁UN 2113
2115
+ BEL 2114
2116
+ V 2115
2117
+ ▁AFFORD 2116
2118
+ ▁AIR 2117
2119
+ ▁DOG 2118
2120
+ ▁WALL 2119
2121
+ 耳 2120
2122
+ 聋 2121
2123
+ ▁MU 2122
2124
+ ▁APPLE 2123
2125
+ 堵 2124
2126
+ ▁FLOAT 2125
2127
+ ▁LAKE 2126
2128
+ 虑 2127
2129
+ 鬼 2128
2130
+ 谷 2129
2131
+ 杭 2130
2132
+ ▁FAMILIAR 2131
2133
+ ▁PAIR 2132
2134
+ 铝 2133
2135
+ 隔 2134
2136
+ 扫 2135
2137
+ ▁CLEAN 2136
2138
+ 揪 2137
2139
+ ▁SIT 2138
2140
+ ▁SAT 2139
2141
+ 弹 2140
2142
+ ▁TALK 2141
2143
+ ▁SORT 2142
2144
+ ▁THING 2143
2145
+ ▁FOOLISH 2144
2146
+ ▁THOUGHT 2145
2147
+ 齐 2146
2148
+ ▁LESSON 2147
2149
+ ▁CHOOSE 2148
2150
+ ▁MAIN 2149
2151
+ ▁POINT 2150
2152
+ ▁ACHIEVEMENT 2151
2153
+ 谊 2152
2154
+ 船 2153
2155
+ ▁CAP 2154
2156
+ IZ 2155
2157
+ ▁LITTLE 2156
2158
+ 裙 2157
2159
+ ▁GUIDE 2158
2160
+ ▁IMPOSSIBLE 2159
2161
+ 胳 2160
2162
+ 膊 2161
2163
+ 矮 2162
2164
+ ▁ANGRY 2163
2165
+ CO 2164
2166
+ ▁FAR 2165
2167
+ ▁REASON 2166
2168
+ ▁BASKET 2167
2169
+ ▁LISTEN 2168
2170
+ ▁LAW 2169
2171
+ ▁ARGU 2170
2172
+ MENT 2171
2173
+ ▁TREAT 2172
2174
+ ▁TREATMENT 2173
2175
+ ▁UNKNOWN 2174
2176
+ ▁FIX 2175
2177
+ UP 2176
2178
+ 浇 2177
2179
+ 京 2178
2180
+ 赶 2179
2181
+ ▁DRESSED 2180
2182
+ 绯 2181
2183
+ ▁EVER 2182
2184
+ 永 2183
2185
+ ▁MISTER 2184
2186
+ ▁SMITH 2185
2187
+ ▁SH 2186
2188
+ ▁FLAG 2187
2189
+ 竖 2188
2190
+ 祖 2189
2191
+ ▁BROUGHT 2190
2192
+ OW 2191
2193
+ AB 2192
2194
+ OUT 2193
2195
+ ▁ACCIDENT 2194
2196
+ ▁END 2195
2197
+ 洁 2196
2198
+ ▁BIRTH 2197
2199
+ ▁PARTY 2198
2200
+ 寻 2199
2201
+ 执 2200
2202
+ ▁MOOD 2201
2203
+ 祝 2202
2204
+ 设 2203
2205
+ ▁ABANDON 2204
2206
+ ▁THROUGH 2205
2207
+ ▁TIMES 2206
2208
+ ▁PLANS 2207
2209
+ ▁ANNOUNCED 2208
2210
+ ▁TIGER 2209
2211
+ 繁 2210
2212
+ SCAR 2211
2213
+ 哥 2212
2214
+ 逼 2213
2215
+ 沮 2214
2216
+ 丧 2215
2217
+ ▁SENSITIVE 2216
2218
+ ▁CO 2217
2219
+ ▁BIG 2218
2220
+ ▁DEAL 2219
2221
+ LESS 2220
2222
+ ▁COMPANY 2221
2223
+ ▁CHANGE 2222
2224
+ ▁MONTH 2223
2225
+ ▁PLAYING 2224
2226
+ ▁BOOKS 2225
2227
+ ▁TEACH 2226
2228
+ ▁ROOT 2227
2229
+ ▁ARRIVAL 2228
2230
+ 独 2229
2231
+ ▁BEAUTIFUL 2230
2232
+ 漂 2231
2233
+ ▁MEAN 2232
2234
+ ▁INTEND 2233
2235
+ ▁SUPPOSE 2234
2236
+ HAM 2235
2237
+ ▁ASHAMED 2236
2238
+ ▁MODEL 2237
2239
+ ▁PLAN 2238
2240
+ ▁CHINESE 2239
2241
+ ▁IDEA 2240
2242
+ ▁POLICE 2241
2243
+ 革 2242
2244
+ ▁FIFTH 2243
2245
+ 虚 2244
2246
+ 楼 2245
2247
+ 寓 2246
2248
+ ▁BAD 2247
2249
+ 壮 2248
2250
+ ▁DECIDE 2249
2251
+ ▁COLOUR 2250
2252
+ ▁YELLOW 2251
2253
+ ▁BLUE 2252
2254
+ ▁BROWN 2253
2255
+ 酒 2254
2256
+ ▁OIL 2255
2257
+ ▁RESOURCE 2256
2258
+ 源 2257
2259
+ ▁AUDIENCE 2258
2260
+ 拎 2259
2261
+ 伦 2260
2262
+ 敦 2261
2263
+ 铁 2262
2264
+ ▁VISITOR 2263
2265
+ 仅 2264
2266
+ ▁USEFUL 2265
2267
+ ▁MENTAL 2266
2268
+ ▁ILL 2267
2269
+ ▁LOSE 2268
2270
+ ▁SWEEP 2269
2271
+ ▁EXPECT 2270
2272
+ ▁PRESIDENT 2271
2273
+ ▁ADVICE 2272
2274
+ 匀 2273
2275
+ 绿 2274
2276
+ 浊 2275
2277
+ ▁DIS 2276
2278
+ 颁 2277
2279
+ 卖 2278
2280
+ 弃 2279
2281
+ ▁ANYWHERE 2280
2282
+ ▁SMELL 2281
2283
+ 斩 2282
2284
+ 购 2283
2285
+ 严 2284
2286
+ 谨 2285
2287
+ ▁INTER 2286
2288
+ ID 2287
2289
+ 青 2288
2290
+ ▁FORWARD 2289
2291
+ ▁CAME 2290
2292
+ ▁AGAIN 2291
2293
+ 贵 2292
2294
+ IST 2293
2295
+ ▁BOSTON 2294
2296
+ 暴 2295
2297
+ ▁HAIR 2296
2298
+ 雨 2297
2299
+ 伞 2298
2300
+ ▁CONFIDENCE 2299
2301
+ ▁WHISTL 2300
2302
+ EN 2301
2303
+ 摄 2302
2304
+ 肃 2303
2305
+ ▁SERIOUS 2304
2306
+ 急 2305
2307
+ 戴 2306
2308
+ 帽 2307
2309
+ 穿 2308
2310
+ 衣 2309
2311
+ 嘶 2310
2312
+ 哭 2311
2313
+ ▁DRESS 2312
2314
+ 寄 2313
2315
+ ▁RECEIVE 2314
2316
+ ▁ARRIVE 2315
2317
+ 聪 2316
2318
+ ▁GAIN 2317
2319
+ ▁WIN 2318
2320
+ ▁TIRED 2319
2321
+ ▁JANUARY 2320
2322
+ ▁FEBRUARY 2321
2323
+ ▁MARCH 2322
2324
+ ▁APRIL 2323
2325
+ 龄 2324
2326
+ ▁USE 2325
2327
+ 监 2326
2328
+ ▁SNOW 2327
2329
+ 哇 2328
2330
+ ▁PETER 2329
2331
+ ▁DANGEROUS 2330
2332
+ 妖 2331
2333
+ ▁CATCH 2332
2334
+ 玻 2333
2335
+ 璃 2334
2336
+ 班 2335
2337
+ ATE 2336
2338
+ 申 2337
2339
+ 舍 2338
2340
+ ▁SAYING 2339
2341
+ ▁ASKED 2340
2342
+ ▁NAME 2341
2343
+ ▁CONSULT 2342
2344
+ ▁NEWS 2343
2345
+ ▁MI 2344
2346
+ 麦 2345
2347
+ 醒 2346
2348
+ ▁DIFFERENT 2347
2349
+ 扇 2348
2350
+ 尺 2349
2351
+ ▁GRATEFUL 2350
2352
+ LO 2351
2353
+ CK 2352
2354
+ ▁LOCK 2353
2355
+ 锁 2354
2356
+ 轴 2355
2357
+ 顶 2356
2358
+ 娜 2357
2359
+ 吝 2358
2360
+ 啬 2359
2361
+ 火 2360
2362
+ ▁EXPERIMENT 2361
2363
+ ▁DEAF 2362
2364
+ ▁YEAR 2363
2365
+ ▁PRIVATE 2364
2366
+ 村 2365
2367
+ 庄 2366
2368
+ ▁OPPOS 2367
2369
+ 奏 2368
2370
+ ▁CASE 2369
2371
+ ▁LEAST 2370
2372
+ ▁CHANCE 2371
2373
+ 谢 2372
2374
+ ▁LOW 2373
2375
+ 泳 2374
2376
+ ▁SWIM 2375
2377
+ ▁SUPPORT 2376
2378
+ ▁PERSUADE 2377
2379
+ 哒 2378
2380
+ 凯 2379
2381
+ 拽 2380
2382
+ 宿 2381
2383
+ 刘 2382
2384
+ 寿 2383
2385
+ 虎 2384
2386
+ 妞 2385
2387
+ 祥 2386
2388
+ 巩 2387
2389
+ 堆 2388
2390
+ SE 2389
2391
+ LF 2390
2392
+ 溺 2391
2393
+ ▁TEN 2392
2394
+ 您 2393
2395
+ ▁RESTAURANT 2394
2396
+ 蛮 2395
2397
+ ▁STAR 2396
2398
+ 盯 2397
2399
+ 枯 2398
2400
+ 燥 2399
2401
+ 兴 2400
2402
+ 趣 2401
2403
+ ▁LATE 2402
2404
+ ▁COMPETITOR 2403
2405
+ 竞 2404
2406
+ 纪 2405
2407
+ 爽 2406
2408
+ ▁EX 2407
2409
+ 末 2408
2410
+ ▁TRIP 2409
2411
+ 蜿 2410
2412
+ 蜒 2411
2413
+ 曲 2412
2414
+ 羞 2413
2415
+ 耻 2414
2416
+ 贡 2415
2417
+ 献 2416
2418
+ ▁MONTHS 2417
2419
+ GO 2418
2420
+ ▁SENTENCE 2419
2421
+ ▁BATH 2420
2422
+ HE 2421
2423
+ ▁RUNN 2422
2424
+ TI 2423
2425
+ ▁KEEPING 2424
2426
+ ▁GATE 2425
2427
+ ▁MASTER 2426
2428
+ 挂 2427
2429
+ ▁PERSONAL 2428
2430
+ ▁ALMO 2429
2431
+ 冲 2430
2432
+ ▁ELSE 2431
2433
+ 索 2432
2434
+ ▁VOL 2433
2435
+ UN 2434
2436
+ TE 2435
2437
+ 沦 2436
2438
+ 浸 2437
2439
+ ▁VIEW 2438
2440
+ 癌 2439
2441
+ 症 2440
2442
+ ▁EVEN 2441
2443
+ ▁SAY 2442
2444
+ 财 2443
2445
+ 府 2444
2446
+ ▁WISHES 2445
2447
+ ▁PREVENT 2446
2448
+ 阻 2447
2449
+ ▁PRACTICE 2448
2450
+ ▁MAKES 2449
2451
+ 遵 2450
2452
+ ▁ENGINEER 2451
2453
+ ▁EN 2452
2454
+ 集 2453
2455
+ ▁MOVE 2454
2456
+ ▁MOVED 2455
2457
+ ▁CLEAR 2456
2458
+ FULLY 2457
2459
+ ▁SETTLE 2458
2460
+ 督 2459
2461
+ 促 2460
2462
+ ▁NEIGHBOR 2461
2463
+ ▁CALLED 2462
2464
+ ▁NERVOUS 2463
2465
+ 粤 2464
2466
+ 版 2465
2467
+ 派 2466
2468
+ ▁FIGURE 2467
2469
+ ▁HOLIDAY 2468
2470
+ ▁THUS 2469
2471
+ ▁DIE 2470
2472
+ ▁HEARD 2471
2473
+ ▁ALONE 2472
2474
+ ▁LONE 2473
2475
+ 王 2474
2476
+ ▁RATHER 2475
2477
+ 层 2476
2478
+ ▁VER 2477
2479
+ 终 2478
2480
+ ▁BRAVE 2479
2481
+ 蜜 2480
2482
+ 蜂 2481
2483
+ ▁HONEY 2482
2484
+ 甜 2483
2485
+ ▁CLOTH 2484
2486
+ ▁CH 2485
2487
+ OR 2486
2488
+ ▁WALK 2487
2489
+ ▁BECAME 2488
2490
+ ▁KNOWN 2489
2491
+ ▁TRUE 2490
2492
+ ES 2491
2493
+ 役 2492
2494
+ 植 2493
2495
+ ▁APPEAR 2494
2496
+ ▁LIE 2495
2497
+ ▁REMAIN 2496
2498
+ 卓 2497
2499
+ ▁LUCK 2498
2500
+ ILY 2499
2501
+ UCK 2500
2502
+ ▁MUS 2501
2503
+ 博 2502
2504
+ 馆 2503
2505
+ ▁PAINT 2504
2506
+ 奋 2505
2507
+ ▁DISAGREE 2506
2508
+ 松 2507
2509
+ 烤 2508
2510
+ 箱 2509
2511
+ 温 2510
2512
+ SIDE 2511
2513
+ ▁CRY 2512
2514
+ 金 2513
2515
+ 端 2514
2516
+ 唯 2515
2517
+ ▁BOUGHT 2516
2518
+ ▁BUY 2517
2519
+ ▁TA 2518
2520
+ ▁FOOD 2519
2521
+ 艘 2520
2522
+ ▁LEST 2521
2523
+ ▁JOB 2522
2524
+ 抛 2523
2525
+ ▁JE 2524
2526
+ ▁SANG 2525
2527
+ ▁JUST 2526
2528
+ ▁PLAYED 2527
2529
+ ▁YESTERDAY 2528
2530
+ ▁AFTERNOON 2529
2531
+ 药 2530
2532
+ 狐 2531
2533
+ 狸 2532
2534
+ ▁CRITIC 2533
2535
+ 批 2534
2536
+ 评 2535
2537
+ 碳 2536
2538
+ 拆 2537
2539
+ ▁WHETHER 2538
2540
+ ▁HID 2539
2541
+ ▁HIDDEN 2540
2542
+ 穴 2541
2543
+ ▁SHIRT 2542
2544
+ 址 2543
2545
+ 渐 2544
2546
+ ▁PRETTY 2545
2547
+ ▁SHEEP 2546
2548
+ 逝 2547
2549
+ 逃 2548
2550
+ ▁WHEEL 2549
2551
+ 幕 2550
2552
+ 睛 2551
2553
+ ▁HIND 2552
2554
+ ▁TREES 2553
2555
+ ▁WORRY 2554
2556
+ 凭 2555
2557
+ ▁TOMORROW 2556
2558
+ 浙 2557
2559
+ ▁QUESTION 2558
2560
+ ▁MISS 2559
2561
+ 亡 2560
2562
+ 智 2561
2563
+ AR 2562
2564
+ ▁KNIFE 2563
2565
+ 刀 2564
2566
+ ▁BIGGE 2565
2567
+ ▁DAN 2566
2568
+ ▁FRIDAY 2567
2569
+ 云 2568
2570
+ ▁BOARD 2569
2571
+ 跃 2570
2572
+ 沿 2571
2573
+ 鹊 2572
2574
+ ▁THINGS 2573
2575
+ 综 2574
2576
+ ▁TRYING 2575
2577
+ ▁SWAM 2576
2578
+ ▁SWU 2577
2579
+ ▁FLY 2578
2580
+ ▁FLEW 2579
2581
+ ▁DATE 2580
2582
+ 忽 2581
2583
+ 嫩 2582
2584
+ ▁LIGHT 2583
2585
+ ▁WHOSE 2584
2586
+ ▁INCREASING 2585
2587
+ ▁MAGIC 2586
2588
+ ▁REFER 2587
2589
+ ▁HISTORIC 2588
2590
+ 施 2589
2591
+ 估 2590
2592
+ SOME 2591
2593
+ 苹 2592
2594
+ 旁 2593
2595
+ ▁WEATHER 2594
2596
+ ▁CREAT 2595
2597
+ 拨 2596
2598
+ 茧 2597
2599
+ 蝉 2598
2600
+ 呈 2599
2601
+ 局 2600
2602
+ 欧 2601
2603
+ 洲 2602
2604
+ ▁DISAPPOINT 2603
2605
+ 垃 2604
2606
+ 圾 2605
2607
+ ▁HAPPY 2606
2608
+ ▁WAITING 2607
2609
+ ▁TRY 2608
2610
+ 恤 2609
2611
+ 衫 2610
2612
+ 寂 2611
2613
+ 妹 2612
2614
+ ▁BETWEEN 2613
2615
+ ▁LATER 2614
2616
+ ▁CONTACT 2615
2617
+ ▁TWENTY 2616
2618
+ 饿 2617
2619
+ ▁BEHAV 2618
2620
+ ▁WA 2619
2621
+ DEN 2620
2622
+ 偶 2621
2623
+ 罚 2622
2624
+ ITY 2623
2625
+ 壤 2624
2626
+ 峡 2625
2627
+ ▁NOVEMBER 2626
2628
+ ▁DECEMBER 2627
2629
+ ▁REMAINED 2628
2630
+ ▁GRAND 2629
2631
+ PAR 2630
2632
+ 仍 2631
2633
+ ▁HABIT 2632
2634
+ 租 2633
2635
+ ▁RED 2634
2636
+ IR 2635
2637
+ ▁PLATE 2636
2638
+ ▁BOTTLE 2637
2639
+ VE 2638
2640
+ 狼 2639
2641
+ ▁WOLF 2640
2642
+ 附 2641
2643
+ 欲 2642
2644
+ 抑 2643
2645
+ 司 2644
2646
+ ▁DRIVER 2645
2647
+ 仿 2646
2648
+ VER 2647
2649
+ 兄 2648
2650
+ 弟 2649
2651
+ 叔 2650
2652
+ ▁PASSENGER 2651
2653
+ ▁RAIL 2652
2654
+ 轨 2653
2655
+ ▁EMOTION 2654
2656
+ ▁DEFI 2655
2657
+ IES 2656
2658
+ ▁WOOD 2657
2659
+ LU 2658
2660
+ AG 2659
2661
+ PH 2660
2662
+ FICIENCY 2661
2663
+ ▁OH 2662
2664
+ ▁GOD 2663
2665
+ 删 2664
2666
+ ▁ROPE 2665
2667
+ ▁DETERMINED 2666
2668
+ ▁WRONG 2667
2669
+ ▁PRICE 2668
2670
+ 川 2669
2671
+ 阱 2670
2672
+ 北 2671
2673
+ ▁STANDING 2672
2674
+ 倘 2673
2675
+ CON 2674
2676
+ RO 2675
2677
+ ▁GAME 2676
2678
+ ▁COMES 2677
2679
+ 压 2678
2680
+ 厨 2679
2681
+ 拟 2680
2682
+ 浓 2681
2683
+ ▁CONDITION 2682
2684
+ ▁BAG 2683
2685
+ ▁DOLLARS 2684
2686
+ ▁CAUTIOUS 2685
2687
+ ▁CAUTION 2686
2688
+ ▁CORRECT 2687
2689
+ ▁THOSE 2688
2690
+ ▁REVIEW 2689
2691
+ 兀 2690
2692
+ 呗 2691
2693
+ 丙 2692
2694
+ 浩 2693
2695
+ 猫 2694
2696
+ ▁SPEECH 2695
2697
+ TERN 2696
2698
+ ▁FLIGHT 2697
2699
+ ▁STOPPING 2698
2700
+ 扰 2699
2701
+ 届 2700
2702
+ ▁SEAL 2701
2703
+ 封 2702
2704
+ 袋 2703
2705
+ 炸 2704
2706
+ 驴 2705
2707
+ 扯 2706
2708
+ ▁POWER 2707
2709
+ ▁ELECTRIC 2708
2710
+ 咬 2709
2711
+ 舌 2710
2712
+ ▁KISS 2711
2713
+ ▁PICTURE 2712
2714
+ 憋 2713
2715
+ 胆 2714
2716
+ ▁ENORMOUS 2715
2717
+ ▁DUTY 2716
2718
+ 卫 2717
2719
+ 废 2718
2720
+ 鸡 2719
2721
+ 溪 2720
2722
+ ▁EXPLAIN 2721
2723
+ 宫 2722
2724
+ 殿 2723
2725
+ ▁PALACE 2724
2726
+ ▁MINE 2725
2727
+ 障 2726
2728
+ 碍 2727
2729
+ HOW 2728
2730
+ AM 2729
2731
+ 阮 2730
2732
+ ▁CARRY 2731
2733
+ 透 2732
2734
+ ▁HOLE 2733
2735
+ 拓 2734
2736
+ ▁IMPRESS 2735
2737
+ ▁DREAMS 2736
2738
+ HOLD 2737
2739
+ ▁CRAFT 2738
2740
+ 彼 2739
2741
+ AC 2740
2742
+ 乒 2741
2743
+ 乓 2742
2744
+ ▁ALONG 2743
2745
+ ▁DIED 2744
2746
+ ▁DY 2745
2747
+ ▁REPAIR 2746
2748
+ ▁EVERYBODY 2747
2749
+ ▁KNOWS 2748
2750
+ 奥 2749
2751
+ MP 2750
2752
+ ▁PREFER 2751
2753
+ ACK 2752
2754
+ ▁PACK 2753
2755
+ ▁SYSTEM 2754
2756
+ QUI 2755
2757
+ 迹 2756
2758
+ ▁POPULAR 2757
2759
+ ▁ANYBODY 2758
2760
+ 订 2759
2761
+ 访 2760
2762
+ ▁UNTIL 2761
2763
+ 橘 2762
2764
+ ▁HONOR 2763
2765
+ 歘 2764
2766
+ 欻 2765
2767
+ ▁EASI 2766
2768
+ 寞 2767
2769
+ ▁GENERAL 2768
2770
+ ▁LATTER 2769
2771
+ 挖 2770
2772
+ 裁 2771
2773
+ 叙 2772
2774
+ ▁KILL 2773
2775
+ 赘 2774
2776
+ ▁UNITED 2775
2777
+ 倡 2776
2778
+ ▁FORGIVE 2777
2779
+ 谅 2778
2780
+ 盖 2779
2781
+ 涵 2780
2782
+ 晕 2781
2783
+ ▁TELEPHONE 2782
2784
+ ▁DISTANCE 2783
2785
+ 侧 2784
2786
+ 锥 2785
2787
+ 摔 2786
2788
+ 啃 2787
2789
+ ▁SKIRT 2788
2790
+ ▁SU 2789
2791
+ ▁SISTER 2790
2792
+ 愁 2791
2793
+ 扔 2792
2794
+ 询 2793
2795
+ 匹 2794
2796
+ ITE 2795
2797
+ 拍 2796
2798
+ ▁SMART 2797
2799
+ ▁REALIZE 2798
2800
+ ▁WHATEVER 2799
2801
+ ▁SPIRIT 2800
2802
+ NESS 2801
2803
+ ▁DARK 2802
2804
+ COGNI 2803
2805
+ 朝 2804
2806
+ 南 2805
2807
+ ▁PLACE 2806
2808
+ 摇 2807
2809
+ 诺 2808
2810
+ ▁INTERESTING 2809
2811
+ 盘 2810
2812
+ ▁BRUSH 2811
2813
+ ▁TEETH 2812
2814
+ 烟 2813
2815
+ ▁PARK 2814
2816
+ ▁WASH 2815
2817
+ ▁CLOTHES 2816
2818
+ ▁LA 2817
2819
+ UND 2818
2820
+ 呆 2819
2821
+ 烦 2820
2822
+ 悔 2821
2823
+ ▁NEXT 2822
2824
+ ▁DOOR 2823
2825
+ ▁BAL 2824
2826
+ 苏 2825
2827
+ ▁TRUTH 2826
2828
+ ▁BALL 2827
2829
+ 添 2828
2830
+ ▁STOMACH 2829
2831
+ CHE 2830
2832
+ ▁AFRAID 2831
2833
+ 陌 2832
2834
+ 糖 2833
2835
+ ▁DEVELOP 2834
2836
+ ▁COUNTRIES 2835
2837
+ 巾 2836
2838
+ ▁TAKING 2837
2839
+ 吩 2838
2840
+ 咐 2839
2841
+ ▁SITUATION 2840
2842
+ 匠 2841
2843
+ ▁TALENT 2842
2844
+ 汁 2843
2845
+ ▁WON 2844
2846
+ ▁NOWADAYS 2845
2847
+ ▁SURE 2846
2848
+ ▁MOR 2847
2849
+ ▁WANTED 2848
2850
+ 缉 2849
2851
+ ▁REWARD 2850
2852
+ 悬 2851
2853
+ 赏 2852
2854
+ ▁BELOW 2853
2855
+ ▁PI 2854
2856
+ 蒙 2855
2857
+ ▁QUICKLY 2856
2858
+ ▁ALREADY 2857
2859
+ 搜 2858
2860
+ 恼 2859
2861
+ ▁LONGER 2860
2862
+ ▁ADMIRE 2861
2863
+ 噔 2862
2864
+ 伙 2863
2865
+ 未 2864
2866
+ 猴 2865
2867
+ ▁MONKEY 2866
2868
+ ▁INCLUD 2867
2869
+ ▁STARTED 2868
2870
+ ▁OFFICE 2869
2871
+ 彩 2870
2872
+ 殆 2871
2873
+ ▁BECOME 2872
2874
+ IG 2873
2875
+ 陪 2874
2876
+ 伴 2875
2877
+ 旋 2876
2878
+ ▁FINE 2877
2879
+ 冗 2878
2880
+ 稿 2879
2881
+ DER 2880
2882
+ ▁THOUSAND 2881
2883
+ ▁POUND 2882
2884
+ ▁SHIP 2883
2885
+ ▁RISE 2884
2886
+ 逐 2885
2887
+ ▁TRAVEL 2886
2888
+ 幼 2887
2889
+ 喊 2888
2890
+ 罗 2889
2891
+ 斯 2890
2892
+ ▁LETTER 2891
2893
+ 噻 2892
2894
+ 牌 2893
2895
+ 瓶 2894
2896
+ 豪 2895
2897
+ 炉 2896
2898
+ NG 2897
2899
+ ▁FRUIT 2898
2900
+ IM 2899
2901
+ ▁EAT 2900
2902
+ ▁TWELVE 2901
2903
+ ▁SAND 2902
2904
+ WI 2903
2905
+ ▁LUNCH 2904
2906
+ ▁MOON 2905
2907
+ HER 2906
2908
+ 操 2907
2909
+ ▁FRIENDSHIP 2908
2910
+ 凝 2909
2911
+ ▁CAMP 2910
2912
+ 营 2911
2913
+ ▁NATURAL 2912
2914
+ 优 2913
2915
+ 疫 2914
2916
+ 衡 2915
2917
+ 苗 2916
2918
+ 斜 2917
2919
+ ▁AMUSEMENT 2918
2920
+ ▁CHECK 2919
2921
+ ▁APPLY 2920
2922
+ 梳 2921
2923
+ ▁NINE 2922
2924
+ ▁NINETEEN 2923
2925
+ 珍 2924
2926
+ ▁BREAKFAST 2925
2927
+ ▁SILENT 2926
2928
+ ▁CHA 2927
2929
+ 夜 2928
2930
+ ▁WORDS 2929
2931
+ 惨 2930
2932
+ ▁DIFFICULT 2931
2933
+ 囊 2932
2934
+ TON 2933
2935
+ ▁KNOCK 2934
2936
+ ▁CONCERN 2935
2937
+ 贱 2936
2938
+ 仁 2937
2939
+ ▁DIFFERENCE 2938
2940
+ 魅 2939
2941
+ ▁CHARM 2940
2942
+ ▁DINNER 2941
2943
+ ▁SUPPER 2942
2944
+ 餐 2943
2945
+ ▁MEANTIME 2944
2946
+ 即 2945
2947
+ ▁LOOKING 2946
2948
+ ▁SEEING 2947
2949
+ ▁EDUCATION 2948
2950
+ ▁BEGIN 2949
2951
+ IAL 2950
2952
+ 审 2951
2953
+ 暗 2952
2954
+ ▁EFFORT 2953
2955
+ IDE 2954
2956
+ 灭 2955
2957
+ 产 2956
2958
+ ▁REFUSED 2957
2959
+ AUGHT 2958
2960
+ ▁MEET 2959
2961
+ ▁DELAY 2960
2962
+ ▁JUMP 2961
2963
+ ▁EXCITEMENT 2962
2964
+ ADI 2963
2965
+ 钙 2964
2966
+ NO 2965
2967
+ OM 2966
2968
+ 扎 2967
2969
+ 辈 2968
2970
+ ▁BACHELOR 2969
2971
+ ▁AMONG 2970
2972
+ ▁PENCIL 2971
2973
+ ▁SNAKE 2972
2974
+ ▁ANSWERED 2973
2975
+ ▁BIT 2974
2976
+ ▁TONGUE 2975
2977
+ 衔 2976
2978
+ 俄 2977
2979
+ 卵 2978
2980
+ 纲 2979
2981
+ ▁COVER 2980
2982
+ 掩 2981
2983
+ ▁SIMPLE 2982
2984
+ 憎 2983
2985
+ 恶 2984
2986
+ 厌 2985
2987
+ ▁DIRT 2986
2988
+ 脏 2987
2989
+ ▁HU 2988
2990
+ NY 2989
2991
+ 捡 2990
2992
+ ▁STORIES 2991
2993
+ 尴 2992
2994
+ 咨 2993
2995
+ 椅 2994
2996
+ CHA 2995
2997
+ ▁BOX 2996
2998
+ 瞌 2997
2999
+ 睁 2998
3000
+ 澳 2999
3001
+ 亚 3000
3002
+ 吓 3001
3003
+ 均 3002
3004
+ 膝 3003
3005
+ 宝 3004
3006
+ ▁FIFTEEN 3005
3007
+ 棕 3006
3008
+ 墙 3007
3009
+ ▁LIFT 3008
3010
+ 梯 3009
3011
+ ▁MARK 3010
3012
+ 叨 3011
3013
+ 拗 3012
3014
+ ▁COMBIN 3013
3015
+ 颚 3014
3016
+ ▁WEAK 3015
3017
+ ▁STRONG 3016
3018
+ 磅 3017
3019
+ ▁WEIGHT 3018
3020
+ ▁OPINION 3019
3021
+ 鞋 3020
3022
+ ▁GIRLS 3021
3023
+ ▁HIGH 3022
3024
+ ▁SENIOR 3023
3025
+ ▁ATTACK 3024
3026
+ ▁UNCLE 3025
3027
+ ALL 3026
3028
+ ▁FIR 3027
3029
+ 旯 3028
3030
+ ▁REGI 3029
3031
+ RATION 3030
3032
+ 滚 3031
3033
+ 串 3032
3034
+ 耗 3033
3035
+ ▁MATERIAL 3034
3036
+ ▁DESK 3035
3037
+ 箭 3036
3038
+ 县 3037
3039
+ ▁IGNORANCE 3038
3040
+ ▁FUN 3039
3041
+ ▁ORDERS 3040
3042
+ 聚 3041
3043
+ 焦 3042
3044
+ ▁PHRASE 3043
3045
+ ▁RUSH 3044
3046
+ 痕 3045
3047
+ 史 3046
3048
+ ▁ORGAN 3047
3049
+ ▁KEY 3048
3050
+ 焰 3049
3051
+ ▁EDUCAT 3050
3052
+ ▁CAT 3051
3053
+ 异 3052
3054
+ 招 3053
3055
+ 蜗 3054
3056
+ 兔 3055
3057
+ ▁ACT 3056
3058
+ 瓜 3057
3059
+ ▁INTERESTED 3058
3060
+ ▁NEITHER 3059
3061
+ ▁NOR 3060
3062
+ ▁INSIDE 3061
3063
+ ▁LANGUAGE 3062
3064
+ 茶 3063
3065
+ 喷 3064
3066
+ 济 3065
3067
+ ▁SPACE 3066
3068
+ 榜 3067
3069
+ ▁TRAFFIC 3068
3070
+ 衷 3069
3071
+ ▁FELL 3070
3072
+ ▁NATURALLY 3071
3073
+ ▁SECTION 3072
3074
+ ▁OBSERVE 3073
3075
+ ▁PRIM 3074
3076
+ ▁WAIT 3075
3077
+ ▁TRIAL 3076
3078
+ ▁MARRY 3077
3079
+ 眉 3078
3080
+ 塞 3079
3081
+ 渊 3080
3082
+ 氛 3081
3083
+ 涨 3082
3084
+ 氏 3083
3085
+ 赋 3084
3086
+ 赢 3085
3087
+ 雪 3086
3088
+ ▁BORROW 3087
3089
+ ▁BORN 3088
3090
+ ▁AMERICAN 3089
3091
+ ▁DUR 3090
3092
+ NA 3091
3093
+ ▁GRATITUDE 3092
3094
+ 剧 3093
3095
+ 勾 3094
3096
+ ACH 3095
3097
+ ▁SPECIFI 3096
3098
+ 储 3097
3099
+ 银 3098
3100
+ ▁MEANS 3099
3101
+ INESS 3100
3102
+ ▁SIR 3101
3103
+ 烧 3102
3104
+ ▁WOUND 3103
3105
+ 夹 3104
3106
+ ▁JOKE 3105
3107
+ OP 3106
3108
+ 挥 3107
3109
+ 诗 3108
3110
+ 烈 3109
3111
+ ▁CHINA 3110
3112
+ ▁SPRING 3111
3113
+ ▁WORD 3112
3114
+ ▁SERVE 3113
3115
+ ▁UNEXPECTED 3114
3116
+ ▁GRACE 3115
3117
+ ▁SAN 3116
3118
+ UR 3117
3119
+ ▁LARGE 3118
3120
+ ▁SOUL 3119
3121
+ 扑 3120
3122
+ ▁FISHE 3121
3123
+ ▁TWENTIETH 3122
3124
+ ▁TALKING 3123
3125
+ 婆 3124
3126
+ 皂 3125
3127
+ 鸣 3126
3128
+ 盗 3127
3129
+ 挡 3128
3130
+ ▁FOX 3129
3131
+ ▁REMARK 3130
3132
+ 途 3131
3133
+ ▁SPEED 3132
3134
+ ▁GRANDFATHER 3133
3135
+ ▁DANCING 3134
3136
+ ▁DESIRE 3135
3137
+ 渴 3136
3138
+ ▁PICK 3137
3139
+ ▁KNEW 3138
3140
+ ▁SCIENCE 3139
3141
+ ▁SHAKE 3140
3142
+ ▁HANDS 3141
3143
+ 维 3142
3144
+ ▁FUR 3143
3145
+ 艰 3144
3146
+ 泼 3145
3147
+ 盆 3146
3148
+ ▁MARKET 3147
3149
+ ▁QUIET 3148
3150
+ ▁GRASP 3149
3151
+ 咯 3150
3152
+ 权 3151
3153
+ 势 3152
3154
+ ▁REAL 3153
3155
+ ▁BEGINNING 3154
3156
+ ▁LEG 3155
3157
+ 倦 3156
3158
+ ▁BAND 3157
3159
+ LAC 3158
3160
+ ▁HIRE 3159
3161
+ ▁EXPOS 3160
3162
+ ▁DESIGN 3161
3163
+ ▁DICK 3162
3164
+ 俱 3163
3165
+ 库 3164
3166
+ 链 3165
3167
+ ▁LEGS 3166
3168
+ ▁DOLLAR 3167
3169
+ ▁GROWN 3168
3170
+ 刊 3169
3171
+ 挪 3170
3172
+ ▁HEALTH 3171
3173
+ 拒 3172
3174
+ 贯 3173
3175
+ ▁ADDRESS 3174
3176
+ 帝 3175
3177
+ 柴 3176
3178
+ 筑 3177
3179
+ 渔 3178
3180
+ ▁FINALLY 3179
3181
+ ▁DANCE 3180
3182
+ ▁MOUSE 3181
3183
+ 降 3182
3184
+ ▁CELL 3183
3185
+ 胞 3184
3186
+ ▁THEN 3185
3187
+ 庆 3186
3188
+ ▁NATIONAL 3187
3189
+ 猛 3188
3190
+ ▁RUDE 3189
3191
+ ▁STICK 3190
3192
+ ▁RESULT 3191
3193
+ ▁TRUST 3192
3194
+ 亿 3193
3195
+ 芬 3194
3196
+ 芳 3195
3197
+ ▁SMILE 3196
3198
+ ▁EXCUSE 3197
3199
+ 溜 3198
3200
+ 尘 3199
3201
+ 屉 3200
3202
+ ▁FIELD 3201
3203
+ ▁ALICE 3202
3204
+ 宣 3203
3205
+ ▁LADIES 3204
3206
+ ▁GENTLEMEN 3205
3207
+ 棉 3206
3208
+ 驱 3207
3209
+ ▁PENN 3208
3210
+ 恋 3209
3211
+ ▁RUBB 3210
3212
+ ISH 3211
3213
+ 熬 3212
3214
+ 刑 3213
3215
+ 腿 3214
3216
+ ▁EARTH 3215
3217
+ ▁SON 3216
3218
+ ▁FURTHER 3217
3219
+ ▁FREQUENT 3218
3220
+ 烹 3219
3221
+ 饪 3220
3222
+ 胶 3221
3223
+ 渗 3222
3224
+ 毒 3223
3225
+ 咖 3224
3226
+ 啡 3225
3227
+ 授 3226
3228
+ ▁SPEAR 3227
3229
+ ▁OCCASION 3228
3230
+ ▁PROBLEM 3229
3231
+ ▁HIT 3230
3232
+ ▁SMALL 3231
3233
+ ▁FOND 3232
3234
+ 织 3233
3235
+ ▁LONDON 3234
3236
+ 净 3235
3237
+ 磨 3236
3238
+ 晨 3237
3239
+ ▁ANIMAL 3238
3240
+ ▁DUCK 3239
3241
+ ▁BIRDS 3240
3242
+ 揣 3241
3243
+ UGH 3242
3244
+ ▁FLU 3243
3245
+ ▁REPORT 3244
3246
+ ▁INVIT 3245
3247
+ ▁ADMIRATION 3246
3248
+ ▁PUNISH 3247
3249
+ ▁WEST 3248
3250
+ ▁LAND 3249
3251
+ ▁RECEIVED 3250
3252
+ 帆 3251
3253
+ 荆 3252
3254
+ 棘 3253
3255
+ 坎 3254
3256
+ 坷 3255
3257
+ 击 3256
3258
+ 奖 3257
3259
+ 斗 3258
3260
+ ▁STEP 3259
3261
+ 姑 3260
3262
+ ▁ACCOUNT 3261
3263
+ ▁DISCHARG 3262
3264
+ 措 3263
3265
+ ▁MEASURE 3264
3266
+ ▁HUGE 3265
3267
+ 蠢 3266
3268
+ 损 3267
3269
+ ▁TRANQUIL 3268
3270
+ ▁WINTER 3269
3271
+ ▁DESTIN 3270
3272
+ 抻 3271
3273
+ 暑 3272
3274
+ 祸 3273
3275
+ ▁FRONT 3274
3276
+ ▁RUB 3275
3277
+ ▁AGAINST 3276
3278
+ ATING 3277
3279
+ 苍 3278
3280
+ 皱 3279
3281
+ 纹 3280
3282
+ 却 3281
3283
+ ▁FA 3282
3284
+ 佛 3283
3285
+ 顿 3284
3286
+ 杜 3285
3287
+ 甫 3286
3288
+ ▁CONC 3287
3289
+ ▁STRAIGHT 3288
3290
+ 毛 3289
3291
+ ▁WOOL 3290
3292
+ 绪 3291
3293
+ ▁COURSE 3292
3294
+ ▁MATE 3293
3295
+ 斥 3294
3296
+ ▁CALM 3295
3297
+ ▁SHUT 3296
3298
+ ▁FINISHED 3297
3299
+ ▁REACH 3298
3300
+ ▁ARRIVED 3299
3301
+ 枝 3300
3302
+ 茂 3301
3303
+ ▁INFLUENCE 3302
3304
+ ▁BODIES 3303
3305
+ ▁HOLY 3304
3306
+ ▁TOGETHER 3305
3307
+ ▁CHARGE 3306
3308
+ 惕 3307
3309
+ ▁THIRTY 3308
3310
+ ▁JA 3309
3311
+ ▁WELCOME 3310
3312
+ ▁PA 3311
3313
+ DA 3312
3314
+ 熊 3313
3315
+ ▁WAR 3314
3316
+ ▁SHOULDER 3315
3317
+ 港 3316
3318
+ ▁WASHINGTON 3317
3319
+ ▁PLANT 3318
3320
+ ▁RESPONSE 3319
3321
+ 钥 3320
3322
+ 匙 3321
3323
+ ▁EFFECT 3322
3324
+ ▁INVENT 3323
3325
+ IONS 3324
3326
+ ▁LUCY 3325
3327
+ ▁LILY 3326
3328
+ 骨 3327
3329
+ ▁SHOCK 3328
3330
+ ▁BANK 3329
3331
+ 账 3330
3332
+ 档 3331
3333
+ ▁GOLD 3332
3334
+ ▁SWEET 3333
3335
+ ▁INCREASE 3334
3336
+ 杰 3335
3337
+ ▁LO 3336
3338
+ LES 3337
3339
+ 谱 3338
3340
+ ▁ADDITION 3339
3341
+ TER 3340
3342
+ ▁ENERGY 3341
3343
+ ▁INDUSTRY 3342
3344
+ 石 3343
3345
+ ▁LADY 3344
3346
+ 恒 3345
3347
+ ▁FINGER 3346
3348
+ ▁GREW 3347
3349
+ ▁OCEAN 3348
3350
+ CHI 3349
3351
+ 惠 3350
3352
+ 翅 3351
3353
+ ALLY 3352
3354
+ ▁SECRET 3353
3355
+ 秘 3354
3356
+ 捋 3355
3357
+ ▁FOREIGN 3356
3358
+ ▁PREPARATION 3357
3359
+ ▁PRESS 3358
3360
+ URE 3359
3361
+ ▁LION 3360
3362
+ ▁SUCCESSION 3361
3363
+ 卢 3362
3364
+ 衬 3363
3365
+ 嗷 3364
3366
+ 迎 3365
3367
+ 怜 3366
3368
+ ▁SLEEP 3367
3369
+ 迅 3368
3370
+ ▁ASLEEP 3369
3371
+ ▁OPEN 3370
3372
+ ▁MONDAY 3371
3373
+ ▁GROUND 3372
3374
+ ▁RELATION 3373
3375
+ ▁CON 3374
3376
+ NE 3375
3377
+ ARD 3376
3378
+ ▁WAITED 3377
3379
+ ▁HOURS 3378
3380
+ 歧 3379
3381
+ ▁INDEPENDENT 3380
3382
+ 葡 3381
3383
+ 萄 3382
3384
+ 锐 3383
3385
+ 鼻 3384
3386
+ 郊 3385
3387
+ 纵 3386
3388
+ 猩 3387
3389
+ ▁SHOT 3388
3390
+ ▁HEAVY 3389
3391
+ ▁BORE 3390
3392
+ DI 3391
3393
+ ▁SIX 3392
3394
+ ▁BESIDE 3393
3395
+ ▁BESIDES 3394
3396
+ ▁OBVIOUS 3395
3397
+ ▁SINGING 3396
3398
+ ▁ASSOCIAT 3397
3399
+ ▁FIL 3398
3400
+ ▁BLOW 3399
3401
+ 峻 3400
3402
+ ▁ESCAPE 3401
3403
+ ▁CONSIDER 3402
3404
+ 碌 3403
3405
+ 煎 3404
3406
+ 慷 3405
3407
+ 慨 3406
3408
+ ▁DUE 3407
3409
+ 遗 3408
3410
+ 憾 3409
3411
+ ▁LISTENING 3410
3412
+ 粒 3411
3413
+ ▁DELICIOUS 3412
3414
+ 罢 3413
3415
+ ▁INSPIRE 3414
3416
+ ▁INTRODUC 3415
3417
+ GE 3416
3418
+ 淡 3417
3419
+ 龙 3418
3420
+ 予 3419
3421
+ ▁NEGLECT 3420
3422
+ ▁SUFFERING 3421
3423
+ 忠 3422
3424
+ ▁FAITHFUL 3423
3425
+ ▁JUNIOR 3424
3426
+ ▁SHORT 3425
3427
+ 裤 3426
3428
+ ▁EAGER 3427
3429
+ 钠 3428
3430
+ ▁COAT 3429
3431
+ ▁REPLY 3430
3432
+ 欣 3431
3433
+ 慰 3432
3434
+ 瞎 3433
3435
+ 栋 3434
3436
+ ▁HILL 3435
3437
+ ▁PRETEND 3436
3438
+ 赔 3437
3439
+ ▁ROB 3438
3440
+ 抢 3439
3441
+ 劫 3440
3442
+ ▁FILL 3441
3443
+ ▁FORM 3442
3444
+ ▁MILLION 3443
3445
+ 灼 3444
3446
+ ▁VARIOUS 3445
3447
+ 漫 3446
3448
+ 衰 3447
3449
+ ▁SAW 3448
3450
+ 慧 3449
3451
+ 隆 3450
3452
+ 拐 3451
3453
+ ▁CRE 3452
3454
+ ▁INSTANCE 3453
3455
+ 屋 3454
3456
+ ▁DETERMIN 3455
3457
+ ▁EATING 3456
3458
+ ▁FAIL 3457
3459
+ ▁MATCH 3458
3460
+ ▁MEANING 3459
3461
+ 威 3460
3462
+ ▁SAVE 3461
3463
+ ▁SOURCE 3462
3464
+ ▁FOLLOW 3463
3465
+ ▁FALL 3464
3466
+ 跌 3465
3467
+ 货 3466
3468
+ 售 3467
3469
+ ▁NE 3468
3470
+ THER 3469
3471
+ ▁WHEAT 3470
3472
+ 弊 3471
3473
+ 胎 3472
3474
+ ▁NA 3473
3475
+ 缤 3474
3476
+ 纷 3475
3477
+ 斑 3476
3478
+ 斓 3477
3479
+ 冰 3478
3480
+ ▁CLOSING 3479
3481
+ ▁DIRECTION 3480
3482
+ ▁OCCUR 3481
3483
+ 饱 3482
3484
+ 胛 3483
3485
+ ▁AMOUNT 3484
3486
+ ▁COULDN 3485
3487
+ ▁COMPLETE 3486
3488
+ 渤 3487
3489
+ ▁DARE 3488
3490
+ 畴 3489
3491
+ ▁DU 3490
3492
+ ▁OFFICIAL 3491
3493
+ 津 3492
3494
+ ▁MIN 3493
3495
+ 雇 3494
3496
+ ▁FEELING 3495
3497
+ ▁SPORT 3496
3498
+ ▁QUA 3497
3499
+ IFICATION 3498
3500
+ 恨 3499
3501
+ ▁SIMPLY 3500
3502
+ ▁ISLAND 3501
3503
+ 岛 3502
3504
+ ▁BALANC 3503
3505
+ 稣 3504
3506
+ 诞 3505
3507
+ ▁COURAGE 3506
3508
+ 灰 3507
3509
+ 娘 3508
3510
+ ▁AVO 3509
3511
+ ▁COMMUNITY 3510
3512
+ ▁DA 3511
3513
+ ▁UNCONSCIOUS 3512
3514
+ ▁SUPER 3513
3515
+ ▁BEN 3514
3516
+ 迈 3515
3517
+ 遭 3516
3518
+ ▁ADMIT 3517
3519
+ ▁PUPIL 3518
3520
+ 猎 3519
3521
+ 奠 3520
3522
+ ▁HOBB 3521
3523
+ 捕 3522
3524
+ ▁JU 3523
3525
+ ICE 3524
3526
+ ▁ADVANTAGE 3525
3527
+ ▁DISADVANTAGE 3526
3528
+ 臆 3527
3529
+ ▁FARM 3528
3530
+ ▁EYE 3529
3531
+ ▁NEIGHBOURHOOD 3530
3532
+ 糙 3531
3533
+ ▁EVENING 3532
3534
+ ▁LAY 3533
3535
+ 败 3534
3536
+ ▁ALIVE 3535
3537
+ ▁WITNESS 3536
3538
+ 伟 3537
3539
+ 秀 3538
3540
+ ▁WORLD 3539
3541
+ ▁CAKE 3540
3542
+ ▁GLAR 3541
3543
+ ▁EMBARRASS 3542
3544
+ 尬 3543
3545
+ 窘 3544
3546
+ 挨 3545
3547
+ 揍 3546
3548
+ ▁SELL 3547
3549
+ ▁EASY 3548
3550
+ 炮 3549
3551
+ ▁WEEKS 3550
3552
+ ▁COP 3551
3553
+ ▁BELL 3552
3554
+ 菲 3553
3555
+ ▁STATES 3554
3556
+ 凡 3555
3557
+ ▁LOVER 3556
3558
+ 铺 3557
3559
+ ▁USELESS 3558
3560
+ ▁MANAG 3559
3561
+ ▁NORTH 3560
3562
+ ▁INVITATION 3561
3563
+ 邀 3562
3564
+ ▁DROP 3563
3565
+ ▁OFFERED 3564
3566
+ ▁HEAD 3565
3567
+ 鸽 3566
3568
+ 鹅 3567
3569
+ ▁LOWER 3568
3570
+ ▁LAWYER 3569
3571
+ PPED 3570
3572
+ 绑 3571
3573
+ ▁FLOWERS 3572
3574
+ 蹈 3573
3575
+ 膨 3574
3576
+ 胀 3575
3577
+ ▁UNHAPPY 3576
3578
+ 央 3577
3579
+ 洪 3578
3580
+ 追 3579
3581
+ ▁KITCHEN 3580
3582
+ ▁ELECT 3581
3583
+ 乞 3582
3584
+ 丐 3583
3585
+ 阵 3584
3586
+ 喧 3585
3587
+ 雷 3586
3588
+ 峰 3587
3589
+ 嫦 3588
3590
+ 娥 3589
3591
+ ▁INTELLIGENT 3590
3592
+ ▁ANTI 3591
3593
+ ▁GROWING 3592
3594
+ 裕 3593
3595
+ 泡 3594
3596
+ ▁STEAM 3595
3597
+ 蒸 3596
3598
+ 粹 3597
3599
+ 艳 3598
3600
+ ▁CHANGED 3599
3601
+ ▁GIFT 3600
3602
+ ▁EGGS 3601
3603
+ ▁GREATER 3602
3604
+ ▁RARE 3603
3605
+ FT 3604
3606
+ ▁SAFE 3605
3607
+ ▁FATE 3606
3608
+ ▁PR 3607
3609
+ 援 3608
3610
+ ▁INTELLIGENCE 3609
3611
+ STER 3610
3612
+ ▁NOBODY 3611
3613
+ ▁REMIND 3612
3614
+ 捏 3613
3615
+ ▁SHIFT 3614
3616
+ ▁DEATH 3615
3617
+ ▁EAST 3616
3618
+ ▁TRA 3617
3619
+ ▁STA 3618
3620
+ 软 3619
3621
+ 缓 3620
3622
+ ▁SLOW 3621
3623
+ 褴 3622
3624
+ 褛 3623
3625
+ BU 3624
3626
+ ▁AGE 3625
3627
+ 饲 3626
3628
+ ▁HEAVEN 3627
3629
+ 汤 3628
3630
+ 姆 3629
3631
+ 敢 3630
3632
+ 寒 3631
3633
+ QUE 3632
3634
+ ▁HUMOR 3633
3635
+ 幽 3634
3636
+ ▁WHOLE 3635
3637
+ 翔 3636
3638
+ ▁PERFORM 3637
3639
+ GEN 3638
3640
+ RIC 3639
3641
+ ▁BRITISH 3640
3642
+ ▁SOMEWHERE 3641
3643
+ ▁MEANWHILE 3642
3644
+ 碟 3643
3645
+ 淋 3644
3646
+ 浴 3645
3647
+ ▁PROFESSIONAL 3646
3648
+ 嘟 3647
3649
+ 唇 3648
3650
+ ▁JULIA 3649
3651
+ ▁FAIR 3650
3652
+ ▁TAR 3651
3653
+ 厕 3652
3654
+ ▁PATIENT 3653
3655
+ ▁POST 3654
3656
+ ▁APPLI 3655
3657
+ ▁MINUTES 3656
3658
+ 薄 3657
3659
+ 栏 3658
3660
+ 筒 3659
3661
+ 漆 3660
3662
+ ▁SMOOTH 3661
3663
+ ▁SPOKEN 3662
3664
+ 瓢 3663
3665
+ ▁NECESSARY 3664
3666
+ 槽 3665
3667
+ 奴 3666
3668
+ 仆 3667
3669
+ ▁SERVANTS 3668
3670
+ 隶 3669
3671
+ ▁TRU 3670
3672
+ ▁STRANGER 3671
3673
+ ▁ABSENT 3672
3674
+ 席 3673
3675
+ 召 3674
3676
+ 唤 3675
3677
+ 牵 3676
3678
+ 仪 3677
3679
+ ▁BELIEF 3678
3680
+ 梗 3679
3681
+ 筋 3680
3682
+ 媒 3681
3683
+ 刁 3682
3684
+ 钻 3683
3685
+ ▁PERHAPS 3684
3686
+ ▁UNCOMFORTABL 3685
3687
+ ▁COMFORTABLE 3686
3688
+ ▁MULTI 3687
3689
+ ▁READY 3688
3690
+ ▁SEVERAL 3689
3691
+ 雄 3690
3692
+ ▁DECISION 3691
3693
+ NCY 3692
3694
+ 军 3693
3695
+ 泣 3694
3696
+ 屠 3695
3697
+ ▁BUTCHER 3696
3698
+ 滩 3697
3699
+ 堡 3698
3700
+ ▁KEPT 3699
3701
+ 柱 3700
3702
+ 袭 3701
3703
+ 颖 3702
3704
+ ▁WITHOUT 3703
3705
+ 妻 3704
3706
+ 嫁 3705
3707
+ 栖 3706
3708
+ 协 3707
3709
+ 丹 3708
3710
+ 莫 3709
3711
+ 暮 3710
3712
+ 悟 3711
3713
+ ▁DOUBT 3712
3714
+ 莠 3713
3715
+ ▁ADVENTURE 3714
3716
+ ▁FRA 3715
3717
+ 佼 3716
3718
+ 痒 3717
3719
+ 耍 3718
3720
+ ▁TRICK 3719
3721
+ 谋 3720
3722
+ ▁SHOWN 3721
3723
+ ▁STRIV 3722
3724
+ RID 3723
3725
+ ▁HANG 3724
3726
+ ▁SPOKE 3725
3727
+ ▁FOURTH 3726
3728
+ ▁FO 3727
3729
+ 仗 3728
3730
+ 武 3729
3731
+ ▁HAT 3730
3732
+ ▁REGRET 3731
3733
+ HAN 3732
3734
+ ▁NEARLY 3733
3735
+ ▁FRI 3734
3736
+ ▁RANGE 3735
3737
+ ▁SENSE 3736
3738
+ ▁FRANCE 3737
3739
+ ▁MAJOR 3738
3740
+ SPOON 3739
3741
+ 勺 3740
3742
+ ▁LAUGH 3741
3743
+ ▁HARM 3742
3744
+ ▁FLOWER 3743
3745
+ 宏 3744
3746
+ ▁NOVEL 3745
3747
+ 幻 3746
3748
+ ▁PAGE 3747
3749
+ ▁OFFER 3748
3750
+ ▁WI 3749
3751
+ 汗 3750
3752
+ 琴 3751
3753
+ 毯 3752
3754
+ 挣 3753
3755
+ 誉 3754
3756
+ ▁FAILURE 3755
3757
+ 拔 3756
3758
+ ▁MISTAKE 3757
3759
+ TEXT 3758
3760
+ ▁MESSAGE 3759
3761
+ 袜 3760
3762
+ 嘲 3761
3763
+ 琳 3762
3764
+ 居 3763
3765
+ ▁NEIGHBORHOOD 3764
3766
+ ▁WARM 3765
3767
+ 馈 3766
3768
+ ▁MARRIED 3767
3769
+ 啤 3768
3770
+ 盼 3769
3771
+ 凑 3770
3772
+ ▁FROZEN 3771
3773
+ ▁CHOSE 3772
3774
+ ▁CHOSEN 3773
3775
+ ▁PRESENTLY 3774
3776
+ ▁NATIVE 3775
3777
+ ▁ADVANCED 3776
3778
+ ▁DISEASE 3777
3779
+ 荐 3778
3780
+ 怖 3779
3781
+ 艺 3780
3782
+ ▁HELEN 3781
3783
+ ▁DIV 3782
3784
+ ▁DI 3783
3785
+ 甲 3784
3786
+ 婿 3785
3787
+ OES 3786
3788
+ 池 3787
3789
+ ▁BEAR 3788
3790
+ 融 3789
3791
+ ▁QUI 3790
3792
+ LT 3791
3793
+ ▁BROTHER 3792
3794
+ 愤 3793
3795
+ 怒 3794
3796
+ ▁NI 3795
3797
+ LET 3796
3798
+ ▁SKI 3797
3799
+ 矩 3798
3800
+ 笼 3799
3801
+ ▁CERTAINLY 3800
3802
+ ▁PUBLIC 3801
3803
+ ▁DOZEN 3802
3804
+ 铂 3803
3805
+ ▁ABSOLUTE 3804
3806
+ 岸 3805
3807
+ 缘 3806
3808
+ ▁COAST 3807
3809
+ ▁ATTACH 3808
3810
+ 斤 3809
3811
+ AK 3810
3812
+ ▁RELATIVE 3811
3813
+ ▁ENEMY 3812
3814
+ ▁SLAIN 3813
3815
+ 暖 3814
3816
+ ▁YOUNGER 3815
3817
+ 腐 3816
3818
+ 蚀 3817
3819
+ ▁AH 3818
3820
+ ▁SPELL 3819
3821
+ 撒 3820
3822
+ 邻 3821
3823
+ ▁CARRIAGE 3822
3824
+ ▁ANGER 3823
3825
+ ▁BODY 3824
3826
+ ▁HOPED 3825
3827
+ 呸 3826
3828
+ ▁PROVIDE 3827
3829
+ 侥 3828
3830
+ 泉 3829
3831
+ ▁PU 3830
3832
+ KIN 3831
3833
+ ▁SPAR 3832
3834
+ ▁DISCUSSION 3833
3835
+ 谚 3834
3836
+ 涯 3835
3837
+ ▁REGARD 3836
3838
+ 腹 3837
3839
+ PHER 3838
3840
+ ▁BATTER 3839
3841
+ ▁EXPECTATION 3840
3842
+ ▁FUTURE 3841
3843
+ ▁PRINT 3842
3844
+ ▁PERMIT 3843
3845
+ ▁PILOT 3844
3846
+ 紫 3845
3847
+ 旗 3846
3848
+ 帜 3847
3849
+ 玲 3848
3850
+ 叠 3849
3851
+ ▁DRAGON 3850
3852
+ ▁BROKE 3851
3853
+ 毫 3852
3854
+ ▁PRECIOUS 3853
3855
+ 抖 3854
3856
+ 揭 3855
3857
+ 袱 3856
3858
+ 乏 3857
3859
+ ▁SAIL 3858
3860
+ 疗 3859
3861
+ 趋 3860
3862
+ ▁THICK 3861
3863
+ 厚 3862
3864
+ ▁PROUD 3863
3865
+ ▁HIMSELF 3864
3866
+ ▁PORT 3865
3867
+ ▁WINE 3866
3868
+ 踢 3867
3869
+ ▁GARDEN 3868
3870
+ ▁SATISFIED 3869
3871
+ ▁PLACES 3870
3872
+ ▁REFUSE 3871
3873
+ ▁REJECT 3872
3874
+ ▁SWEAT 3873
3875
+ ▁SLOWLY 3874
3876
+ ▁SILVER 3875
3877
+ 铜 3876
3878
+ ▁BRONZE 3877
3879
+ 瞳 3878
3880
+ 侣 3879
3881
+ ▁NOTIC 3880
3882
+ ▁ENGAGE 3881
3883
+ ▁IMAGE 3882
3884
+ 犹 3883
3885
+ 豫 3884
3886
+ ▁SERVICE 3885
3887
+ ▁TRADE 3886
3888
+ 诸 3887
3889
+ ▁VA 3888
3890
+ 歇 3889
3891
+ 兼 3890
3892
+ ▁REALIZED 3891
3893
+ ▁COMMON 3892
3894
+ IER 3893
3895
+ 朵 3894
3896
+ ▁PIECES 3895
3897
+ 樱 3896
3898
+ 桃 3897
3899
+ 亏 3898
3900
+ ▁DELIVER 3899
3901
+ 栀 3900
3902
+ 绵 3901
3903
+ 烫 3902
3904
+ 厅 3903
3905
+ ▁FEATURE 3904
3906
+ ▁BECOMING 3905
3907
+ ▁AVOID 3906
3908
+ ▁TERRIBLE 3907
3909
+ 徐 3908
3910
+ 峥 3909
3911
+ ▁TOUCH 3910
3912
+ 摸 3911
3913
+ 挚 3912
3914
+ ▁HALL 3913
3915
+ ▁SUPPLY 3914
3916
+ ▁PHYSICAL 3915
3917
+ ▁ROSE 3916
3918
+ 骗 3917
3919
+ ▁QUICK 3918
3920
+ ▁FASHION 3919
3921
+ 尚 3920
3922
+ 喻 3921
3923
+ ▁ENCOURAGE 3922
3924
+ ▁MIS 3923
3925
+ ▁MAG 3924
3926
+ 颠 3925
3927
+ 橙 3926
3928
+ 梨 3927
3929
+ 砖 3928
3930
+ ▁BEDROOM 3929
3931
+ ▁ACTIVE 3930
3932
+ 俗 3931
3933
+ ▁INNOCENT 3932
3934
+ 幺 3933
3935
+ ▁HORSE 3934
3936
+ ▁AWAKE 3935
3937
+ ▁WISE 3936
3938
+ ▁BILL 3937
3939
+ ▁TRIED 3938
3940
+ 冻 3939
3941
+ 债 3940
3942
+ 慌 3941
3943
+ 衍 3942
3944
+ ▁JAPANESE 3943
3945
+ ▁EXPENSE 3944
3946
+ 绎 3945
3947
+ ▁HENRY 3946
3948
+ 厘 3947
3949
+ ▁INDEED 3948
3950
+ ▁PINE 3949
3951
+ PP 3950
3952
+ ▁PE 3951
3953
+ ▁STRIKE 3952
3954
+ ▁HOST 3953
3955
+ 嚯 3954
3956
+ 剂 3955
3957
+ ▁ATTRACT 3956
3958
+ ▁MINUTE 3957
3959
+ ▁SURVIV 3958
3960
+ 剪 3959
3961
+ 孟 3960
3962
+ 君 3961
3963
+ 盲 3962
3964
+ ▁AUGUST 3963
3965
+ ▁PATH 3964
3966
+ ▁PRO 3965
3967
+ ▁DAILY 3966
3968
+ ▁STEPP 3967
3969
+ 葱 3968
3970
+ 圣 3969
3971
+ ▁INSECT 3970
3972
+ 昆 3971
3973
+ 虫 3972
3974
+ ▁FORGOT 3973
3975
+ 墅 3974
3976
+ 惬 3975
3977
+ 闯 3976
3978
+ ▁NOSE 3977
3979
+ 镇 3978
3980
+ ▁GIVEN 3979
3981
+ 柯 3980
3982
+ ▁PLEASANT 3981
3983
+ ▁ROME 3982
3984
+ 烂 3983
3985
+ ▁CLA 3984
3986
+ ▁ALLOWED 3985
3987
+ ▁CONVERSATION 3986
3988
+ ▁LAUNCH 3987
3989
+ ▁PROJECT 3988
3990
+ ▁EYES 3989
3991
+ OUR 3990
3992
+ ▁ALTER 3991
3993
+ ▁AGREED 3992
3994
+ 覆 3993
3995
+ 玄 3994
3996
+ 抹 3995
3997
+ ▁STILL 3996
3998
+ ▁PILE 3997
3999
+ 桩 3998
4000
+ ▁HEAVI 3999
4001
+ ▁EXAMINATION 4000
4002
+ 轩 4001
4003
+ ▁BARBER 4002
4004
+ ▁LOVE 4003
4005
+ HIN 4004
4006
+ 伊 4005
4007
+ ▁SHARP 4006
4008
+ 尖 4007
4009
+ 锋 4008
4010
+ 酶 4009
4011
+ ▁GAR 4010
4012
+ TEN 4011
4013
+ ISE 4012
4014
+ ▁FIRE 4013
4015
+ 濒 4014
4016
+ 映 4015
4017
+ ▁JO 4016
4018
+ ▁AVAIL 4017
4019
+ ▁HUNT 4018
4020
+ ▁DECORAT 4019
4021
+ ▁MARY 4020
4022
+ 灾 4021
4023
+ 琐 4022
4024
+ ▁CHATT 4023
4025
+ LINE 4024
4026
+ ▁DISCOVERED 4025
4027
+ ▁SCHOLAR 4026
4028
+ ▁PUBLISH 4027
4029
+ 贺 4028
4030
+ ▁THROAT 4029
4031
+ 喉 4030
4032
+ 咙 4031
4033
+ 咽 4032
4034
+ ▁FACT 4033
4035
+ ▁EXHAUSTED 4034
4036
+ 晦 4035
4037
+ ▁FRANK 4036
4038
+ ▁CHEERFUL 4037
4039
+ 乌 4038
4040
+ 番 4039
4041
+ 茄 4040
4042
+ ▁LEAD 4041
4043
+ ▁LED 4042
4044
+ EM 4043
4045
+ ▁SEARCH 4044
4046
+ ▁QUALITY 4045
4047
+ ▁VOYAGE 4046
4048
+ ▁STAGE 4047
4049
+ MO 4048
4050
+ ▁METAL 4049
4051
+ 驶 4050
4052
+ ▁GOOSE 4051
4053
+ 贼 4052
4054
+ ▁FAMILIES 4053
4055
+ ▁WOR 4054
4056
+ ▁BURN 4055
4057
+ 帐 4056
4058
+ 篷 4057
4059
+ 殖 4058
4060
+ ▁ELEPHANT 4059
4061
+ BOARD 4060
4062
+ 盒 4061
4063
+ ▁TURNING 4062
4064
+ ▁HEARING 4063
4065
+ ▁VEGETABLE 4064
4066
+ ▁RETURN 4065
4067
+ ▁ENTIRE 4066
4068
+ ▁ARMY 4067
4069
+ ▁SYMBOL 4068
4070
+ ▁SCIENTIST 4069
4071
+ ▁BLAME 4070
4072
+ ▁OUTSIDE 4071
4073
+ ▁PRIDE 4072
4074
+ 蝴 4073
4075
+ 蝶 4074
4076
+ ▁PERSONS 4075
4077
+ 抬 4076
4078
+ 砸 4077
4079
+ 仰 4078
4080
+ ▁ACTIVITY 4079
4081
+ 狭 4080
4082
+ ▁BREAKING 4081
4083
+ ▁INDEPENDENCE 4082
4084
+ ▁FANTASTIC 4083
4085
+ 撼 4084
4086
+ ▁OVERCOME 4085
4087
+ ▁WINGS 4086
4088
+ ▁PET 4087
4089
+ 股 4088
4090
+ 绘 4089
4091
+ ▁EXPRESSION 4090
4092
+ 崇 4091
4093
+ ▁COR 4092
4094
+ ORS 4093
4095
+ 呜 4094
4096
+ ▁ADVERTISEMENT 4095
4097
+ 莉 4096
4098
+ ▁DAUGHTER 4097
4099
+ 铃 4098
4100
+ ▁HISTORY 4099
4101
+ 捂 4100
4102
+ 亭 4101
4103
+ ▁UNPLEASANT 4102
4104
+ ▁ADAM 4103
4105
+ ▁DISCIPLINE 4104
4106
+ ▁WAKE 4105
4107
+ ▁RULE 4106
4108
+ ▁ORIGIN 4107
4109
+ ▁ORIGINAL 4108
4110
+ OO 4109
4111
+ 噪 4110
4112
+ ▁ANCIENT 4111
4113
+ 摧 4112
4114
+ 毁 4113
4115
+ ▁MOVING 4114
4116
+ 披 4115
4117
+ 萨 4116
4118
+ 寸 4117
4119
+ 筛 4118
4120
+ ▁NEAR 4119
4121
+ ▁CORNER 4120
4122
+ 诱 4121
4123
+ 饵 4122
4124
+ ▁DISTURB 4123
4125
+ OLI 4124
4126
+ ▁JULY 4125
4127
+ 飘 4126
4128
+ 逸 4127
4129
+ ▁JUNE 4128
4130
+ ▁HELD 4129
4131
+ 憔 4130
4132
+ 悴 4131
4133
+ ▁CARRIE 4132
4134
+ 揉 4133
4135
+ ▁BONES 4134
4136
+ ▁WHIT 4135
4137
+ ▁FOLK 4136
4138
+ 吐 4137
4139
+ 扶 4138
4140
+ ▁CUSHION 4139
4141
+ ▁HAM 4140
4142
+ ▁CURIOSITY 4141
4143
+ 乡 4142
4144
+ ▁GRO 4143
4145
+ ▁TWICE 4144
4146
+ ▁MADAM 4145
4147
+ EVER 4146
4148
+ ▁FORTUNATE 4147
4149
+ ▁FORTUNE 4148
4150
+ LIN 4149
4151
+ ▁REFERENCE 4150
4152
+ ▁SECURE 4151
4153
+ 辩 4152
4154
+ 培 4153
4155
+ ▁CONSIST 4154
4156
+ LLY 4155
4157
+ ▁CONVINCED 4156
4158
+ 莹 4157
4159
+ 凌 4158
4160
+ ▁FALSE 4159
4161
+ ▁RI 4160
4162
+ MORE 4161
4163
+ 寐 4162
4164
+ ▁AWE 4163
4165
+ 晴 4164
4166
+ 雾 4165
4167
+ 澈 4166
4168
+ 翘 4167
4169
+ 射 4168
4170
+ ▁LOOKS 4169
4171
+ ▁DRIVEN 4170
4172
+ ▁BREATH 4171
4173
+ 森 4172
4174
+ 邪 4173
4175
+ ▁SUGGEST 4174
4176
+ 滴 4175
4177
+ ▁MENTIONED 4176
4178
+ 慎 4177
4179
+ ▁NORTHERN 4178
4180
+ ▁INSIST 4179
4181
+ ▁TERM 4180
4182
+ 疯 4181
4183
+ 狂 4182
4184
+ 剖 4183
4185
+ 稚 4184
4186
+ 娱 4185
4187
+ ▁ENTERTAINMENT 4186
4188
+ ▁DEMAND 4187
4189
+ ▁HA 4188
4190
+ ▁GER 4189
4191
+ ▁LAZY 4190
4192
+ 弥 4191
4193
+ 嗝 4192
4194
+ ▁LOUD 4193
4195
+ ▁CLIMB 4194
4196
+ 攀 4195
4197
+ 懵 4196
4198
+ ▁COM 4197
4199
+ ▁APPLAUSE 4198
4200
+ ▁CHARACTER 4199
4201
+ 驾 4200
4202
+ 镑 4201
4203
+ 宗 4202
4204
+ ▁FAVOR 4203
4205
+ 欠 4204
4206
+ 棍 4205
4207
+ ▁NERVE 4206
4208
+ 炎 4207
4209
+ ▁BILLY 4208
4210
+ ▁HOPELESS 4209
4211
+ ▁WORST 4210
4212
+ ▁STUDIED 4211
4213
+ 宠 4212
4214
+ ▁GOVERNMENT 4213
4215
+ ▁CERTAIN 4214
4216
+ 侮 4215
4217
+ 辱 4216
4218
+ ▁WROTE 4217
4219
+ ▁WORSE 4218
4220
+ 糊 4219
4221
+ ▁FELT 4220
4222
+ 殴 4221
4223
+ 垫 4222
4224
+ ▁OBTAIN 4223
4225
+ ▁LIKELY 4224
4226
+ ▁RESOLUTION 4225
4227
+ ▁DETAIL 4226
4228
+ 褐 4227
4229
+ ▁ARTIFICIAL 4228
4230
+ 矿 4229
4231
+ 硝 4230
4232
+ ▁LOG 4231
4233
+ 寝 4232
4234
+ 乔 4233
4235
+ ▁GEORGE 4234
4236
+ ▁QUEEN 4235
4237
+ ▁SOLD 4236
4238
+ 稳 4237
4239
+ 唐 4238
4240
+ 娇 4239
4241
+ ▁ALI 4240
4242
+ ▁SPECIAL 4241
4243
+ ▁HEADS 4242
4244
+ ORY 4243
4245
+ 浆 4244
4246
+ ▁LIMIT 4245
4247
+ ▁ANNOY 4246
4248
+ ▁DAMAGE 4247
4249
+ ▁STOPPED 4248
4250
+ LED 4249
4251
+ ▁GATHER 4250
4252
+ ▁BLOCK 4251
4253
+ 返 4252
4254
+ 舱 4253
4255
+ ▁RELI 4254
4256
+ 旱 4255
4257
+ 骄 4256
4258
+ 傲 4257
4259
+ 伏 4258
4260
+ 骆 4259
4261
+ 驼 4260
4262
+ ▁RESPONSIBLE 4261
4263
+ 扭 4262
4264
+ 徽 4263
4265
+ ▁MYSELF 4264
4266
+ 芽 4265
4267
+ ▁VILLAGE 4266
4268
+ RS 4267
4269
+ 瘾 4268
4270
+ ▁FARMER 4269
4271
+ ▁EIGHTY 4270
4272
+ 瞪 4271
4273
+ ▁EQUAL 4272
4274
+ ▁IMMORTAL 4273
4275
+ ▁FRE 4274
4276
+ ▁FLOW 4275
4277
+ ▁TYPE 4276
4278
+ 嗓 4277
4279
+ ▁GU 4278
4280
+ NEY 4279
4281
+ ▁PIG 4280
4282
+ 绷 4281
4283
+ 欺 4282
4284
+ 籍 4283
4285
+ 窃 4284
4286
+ 卤 4285
4287
+ 舅 4286
4288
+ 炫 4287
4289
+ 耀 4288
4290
+ ▁FLA 4289
4291
+ ▁PL 4290
4292
+ ▁DEAR 4291
4293
+ 瘦 4292
4294
+ 凋 4293
4295
+ HI 4294
4296
+ ▁ADVANCE 4295
4297
+ 搅 4296
4298
+ 拌 4297
4299
+ ▁FIRM 4298
4300
+ ▁POSITION 4299
4301
+ 氨 4300
4302
+ IZED 4301
4303
+ ▁PROPER 4302
4304
+ 遮 4303
4305
+ ▁CONCLUSION 4304
4306
+ 烘 4305
4307
+ 焙 4306
4308
+ ▁DEVOT 4307
4309
+ ▁GREATLY 4308
4310
+ ▁ENTER 4309
4311
+ ▁YOURSELVES 4310
4312
+ ▁GE 4311
4313
+ 湾 4312
4314
+ 滞 4313
4315
+ ▁ENGLAND 4314
4316
+ 噗 4315
4317
+ 罪 4316
4318
+ UDE 4317
4319
+ ▁SEEMED 4318
4320
+ ▁UGLY 4319
4321
+ ▁CRACK 4320
4322
+ ▁CRASH 4321
4323
+ 撞 4322
4324
+ ▁PREPARED 4323
4325
+ ▁DISCOVER 4324
4326
+ 笨 4325
4327
+ 旷 4326
4328
+ 豁 4327
4329
+ 轼 4328
4330
+ 谪 4329
4331
+ 厂 4330
4332
+ ▁SPOT 4331
4333
+ LEY 4332
4334
+ 涤 4333
4335
+ 馏 4334
4336
+ ▁YORK 4335
4337
+ 纽 4336
4338
+ 辐 4337
4339
+ ▁MEANT 4338
4340
+ ▁SLEEPING 4339
4341
+ 浅 4340
4342
+ ▁FIGHT 4341
4343
+ ILE 4342
4344
+ ▁METHOD 4343
4345
+ 曼 4344
4346
+ IA 4345
4347
+ ▁BELIEV 4346
4348
+ ▁BUSI 4347
4349
+ ▁ENABL 4348
4350
+ 陆 4349
4351
+ ▁PREPAR 4350
4352
+ ▁MARTIN 4351
4353
+ ▁SURVEY 4352
4354
+ 渡 4353
4355
+ ▁NEGRO 4354
4356
+ ▁SOFA 4355
4357
+ ▁REGULAR 4356
4358
+ 棋 4357
4359
+ 棵 4358
4360
+ ▁ACCENT 4359
4361
+ ▁LISTENED 4360
4362
+ ▁POLICY 4361
4363
+ ▁SOLUTION 4362
4364
+ 辰 4363
4365
+ 携 4364
4366
+ ▁RECOVER 4365
4367
+ 嘘 4366
4368
+ ▁PERIOD 4367
4369
+ 遥 4368
4370
+ 挫 4369
4371
+ 菇 4370
4372
+ ▁PLEASURE 4371
4373
+ ▁UNIVERSAL 4372
4374
+ 讽 4373
4375
+ ▁SMOK 4374
4376
+ ▁FORBID 4375
4377
+ 巢 4376
4378
+ ▁NEST 4377
4379
+ 俯 4378
4380
+ 撑 4379
4381
+ ▁THEMSELVES 4380
4382
+ ▁EVIL 4381
4383
+ ▁DELICATE 4382
4384
+ ▁ASKING 4383
4385
+ 吹 4384
4386
+ ▁INTERVIEW 4385
4387
+ ▁CARRIED 4386
4388
+ ▁WIND 4387
4389
+ 韩 4388
4390
+ ▁TRAP 4389
4391
+ ▁IMPORTANCE 4390
4392
+ 吻 4391
4393
+ ATIVE 4392
4394
+ ▁JASON 4393
4395
+ ▁LEARNED 4394
4396
+ 皆 4395
4397
+ ▁EVIDENCE 4396
4398
+ 契 4397
4399
+ ▁STARV 4398
4400
+ 酬 4399
4401
+ 抠 4400
4402
+ ▁PERFORMANCE 4401
4403
+ ▁OPERATION 4402
4404
+ 脂 4403
4405
+ 肪 4404
4406
+ ▁HAPPINESS 4405
4407
+ ▁CONDUCT 4406
4408
+ ▁HURRY 4407
4409
+ ▁FAULT 4408
4410
+ ▁GROUP 4409
4411
+ 润 4410
4412
+ 眠 4411
4413
+ ▁GUN 4412
4414
+ ▁PRODUCT 4413
4415
+ 钾 4414
4416
+ ▁PROVE 4415
4417
+ 蒲 4416
4418
+ SERIES 4417
4419
+ 坠 4418
4420
+ 畅 4419
4421
+ 著 4420
4422
+ ▁CLUMS 4421
4423
+ ▁UNUSUAL 4422
4424
+ OMETER 4423
4425
+ ▁LEAVING 4424
4426
+ 宋 4425
4427
+ ▁CHERISH 4426
4428
+ ▁RESCUE 4427
4429
+ 歪 4428
4430
+ ▁HEIGHT 4429
4431
+ 闪 4430
4432
+ 稼 4431
4433
+ 靴 4432
4434
+ ▁ADVIS 4433
4435
+ ARIES 4434
4436
+ 恢 4435
4437
+ LIA 4436
4438
+ 昏 4437
4439
+ 吨 4438
4440
+ ▁STRICT 4439
4441
+ ▁TRADITION 4440
4442
+ 叮 4441
4443
+ 嘱 4442
4444
+ ▁SUR 4443
4445
+ ▁COUSIN 4444
4446
+ 嗨 4445
4447
+ 芙 4446
4448
+ ▁DESIRED 4447
4449
+ 肢 4448
4450
+ 辞 4449
4451
+ 茬 4450
4452
+ 迁 4451
4453
+ ▁RAGE 4452
4454
+ ▁JOE 4453
4455
+ ▁AFRICA 4454
4456
+ ▁GIVING 4455
4457
+ ▁SAFETY 4456
4458
+ ▁RO 4457
4459
+ 燃 4458
4460
+ 亨 4459
4461
+ ▁SPREAD 4460
4462
+ 夺 4461
4463
+ 埋 4462
4464
+ 墓 4463
4465
+ 逍 4464
4466
+ 血 4465
4467
+ ▁WRINKLE 4466
4468
+ ▁DECIDED 4467
4469
+ 玉 4468
4470
+ ▁ALARM 4469
4471
+ 坍 4470
4472
+ 塌 4471
4473
+ 雌 4472
4474
+ ▁WEIGH 4473
4475
+ ▁PASSAGE 4474
4476
+ ▁OBEY 4475
4477
+ ▁HOSPITAL 4476
4478
+ 氯 4477
4479
+ ▁LEATHER 4478
4480
+ 睑 4479
4481
+ ▁SOUTH 4480
4482
+ 丝 4481
4483
+ 掏 4482
4484
+ ▁ART 4483
4485
+ ▁PLENT 4484
4486
+ 劈 4485
4487
+ ▁ROBBER 4486
4488
+ ▁CHAMBER 4487
4489
+ 坦 4488
4490
+ ▁ACCEPT 4489
4491
+ 嘚 4490
4492
+ 摊 4491
4493
+ ▁HO 4492
4494
+ 草 4493
4495
+ 饥 4494
4496
+ 雕 4495
4497
+ 塑 4496
4498
+ 削 4497
4499
+ ▁MOTION 4498
4500
+ 搓 4499
4501
+ 酪 4500
4502
+ 戛 4501
4503
+ ▁MYSTERIOUS 4502
4504
+ 漓 4503
4505
+ 躁 4504
4506
+ 藤 4505
4507
+ ▁CARD 4506
4508
+ ▁VO 4507
4509
+ ▁CONT 4508
4510
+ ▁FRO 4509
4511
+ 庸 4510
4512
+ ▁BRAIN 4511
4513
+ 邦 4512
4514
+ ▁SELECT 4513
4515
+ HOOD 4514
4516
+ ▁FETCH 4515
4517
+ ▁RAN 4516
4518
+ 棱 4517
4519
+ 莎 4518
4520
+ 哄 4519
4521
+ FE 4520
4522
+ ▁DIFFICULTY 4521
4523
+ 吭 4522
4524
+ ▁CHAPTER 4523
4525
+ ▁JOURNEY 4524
4526
+ 廷 4525
4527
+ 潘 4526
4528
+ 帕 4527
4529
+ 牧 4528
4530
+ ▁YARD 4529
4531
+ 咒 4530
4532
+ ▁DETECT 4531
4533
+ ▁PERMISSI 4532
4534
+ ▁CONFESS 4533
4535
+ ▁DEPTH 4534
4536
+ ▁POSSIBILITY 4535
4537
+ ▁IMMEDIATELY 4536
4538
+ 罩 4537
4539
+ ▁REDUC 4538
4540
+ ▁GRANDMOTHER 4539
4541
+ ▁NEVERTHELESS 4540
4542
+ ▁CONF 4541
4543
+ IUS 4542
4544
+ ▁SEASON 4543
4545
+ ▁ENTERTAIN 4544
4546
+ 碱 4545
4547
+ ▁CROWD 4546
4548
+ ▁CROW 4547
4549
+ 粉 4548
4550
+ PI 4549
4551
+ ▁BOUND 4550
4552
+ ▁CANNOT 4551
4553
+ 卑 4552
4554
+ 劣 4553
4555
+ 朱 4554
4556
+ 械 4555
4557
+ ▁STREAM 4556
4558
+ AVING 4557
4559
+ 磁 4558
4560
+ 仇 4559
4561
+ 盟 4560
4562
+ 怨 4561
4563
+ 井 4562
4564
+ 涂 4563
4565
+ 裹 4564
4566
+ ▁VALLEY 4565
4567
+ 陵 4566
4568
+ 撤 4567
4569
+ 仨 4568
4570
+ ▁SPANISH 4569
4571
+ ▁FAILED 4570
4572
+ 旧 4571
4573
+ ▁COUNTER 4572
4574
+ 臂 4573
4575
+ ▁FEAST 4574
4576
+ 宴 4575
4577
+ ▁VENTURE 4576
4578
+ ▁FOREST 4577
4579
+ 捶 4578
4580
+ ▁FER 4579
4581
+ 柏 4580
4582
+ ▁THROW 4581
4583
+ 紊 4582
4584
+ ▁ATTEMPT 4583
4585
+ 蝇 4584
4586
+ ▁THEREFORE 4585
4587
+ ▁SUM 4586
4588
+ ▁HUNGRY 4587
4589
+ ▁SHA 4588
4590
+ 忌 4589
4591
+ ▁AHEAD 4590
4592
+ 韵 4591
4593
+ ▁SUGAR 4592
4594
+ ▁OPENED 4593
4595
+ 氦 4594
4596
+ 锂 4595
4597
+ 铍 4596
4598
+ 硼 4597
4599
+ ▁RELIGION 4598
4600
+ ▁CROWN 4599
4601
+ 筝 4600
4602
+ 聘 4601
4603
+ 欸 4602
4604
+ ▁ASSISTANT 4603
4605
+ 铬 4604
4606
+ ▁ABSENCE 4605
4607
+ ▁SHOWING 4606
4608
+ 淇 4607
4609
+ ▁ICE 4608
4610
+ 阐 4609
4611
+ 麽 4610
4612
+ 霸 4611
4613
+ ▁ANNOUNC 4612
4614
+ ▁STUPID 4613
4615
+ 柔 4614
4616
+ ▁EXPERT 4615
4617
+ ▁FLYING 4616
4618
+ 茫 4617
4619
+ ▁ROCK 4618
4620
+ 祷 4619
4621
+ 缝 4620
4622
+ ▁TRI 4621
4623
+ 割 4622
4624
+ 芒 4623
4625
+ ▁BENEFIT 4624
4626
+ 熄 4625
4627
+ 隙 4626
4628
+ ▁SARAH 4627
4629
+ ▁HATRED 4628
4630
+ ▁DRY 4629
4631
+ ▁VOTE 4630
4632
+ ▁WALKING 4631
4633
+ ▁FLOOR 4632
4634
+ ▁TERMS 4633
4635
+ ▁LEVEL 4634
4636
+ 募 4635
4637
+ 赠 4636
4638
+ 脉 4637
4639
+ 灌 4638
4640
+ RED 4639
4641
+ 迥 4640
4642
+ 泄 4641
4643
+ ▁CONSTANT 4642
4644
+ 懊 4643
4645
+ 催 4644
4646
+ ▁CREATED 4645
4647
+ ▁SPENT 4646
4648
+ 颂 4647
4649
+ IGN 4648
4650
+ ▁BEAT 4649
4651
+ ▁FALLING 4650
4652
+ 颐 4651
4653
+ OV 4652
4654
+ 滋 4653
4655
+ ▁IMPORT 4654
4656
+ ▁BEGUN 4655
4657
+ ▁EXTEND 4656
4658
+ ▁COARSE 4657
4659
+ ▁PAUL 4658
4660
+ 崖 4659
4661
+ NED 4660
4662
+ ▁DIFFER 4661
4663
+ ▁DEVOTED 4662
4664
+ 夕 4663
4665
+ 蛙 4664
4666
+ 丫 4665
4667
+ 蟑 4666
4668
+ 螂 4667
4669
+ ▁PRODUCE 4668
4670
+ ▁CATHERINE 4669
4671
+ ▁PAID 4670
4672
+ 簧 4671
4673
+ 唠 4672
4674
+ 嗑 4673
4675
+ 涌 4674
4676
+ ▁REACTION 4675
4677
+ 鲸 4676
4678
+ 乖 4677
4679
+ 昂 4678
4680
+ 睿 4679
4681
+ ▁INSTITUTION 4680
4682
+ 斧 4681
4683
+ ▁JOINED 4682
4684
+ ▁CLOSED 4683
4685
+ ▁BROTHERS 4684
4686
+ ▁CLOUDS 4685
4687
+ 徘 4686
4688
+ 徊 4687
4689
+ ▁SOFT 4688
4690
+ ▁QUARREL 4689
4691
+ ▁SKILL 4690
4692
+ GUE 4691
4693
+ ▁REQUIRE 4692
4694
+ 茨 4693
4695
+ 梁 4694
4696
+ ▁BURST 4695
4697
+ ▁TEARS 4696
4698
+ ▁LAUGHTER 4697
4699
+ ▁CRYING 4698
4700
+ ▁EXIST 4699
4701
+ 詹 4700
4702
+ 妮 4701
4703
+ ▁FOUGHT 4702
4704
+ 泰 4703
4705
+ 勒 4704
4706
+ 沃 4705
4707
+ 瀑 4706
4708
+ ▁LACK 4707
4709
+ ▁DIRECT 4708
4710
+ ▁LU 4709
4711
+ 贤 4710
4712
+ ▁CRAWL 4711
4713
+ ▁PEPPER 4712
4714
+ 椒 4713
4715
+ 愚 4714
4716
+ 涝 4715
4717
+ ▁FAVOURITE 4716
4718
+ AID 4717
4719
+ ▁FULLY 4718
4720
+ ▁DULL 4719
4721
+ ▁ARRANGEMENT 4720
4722
+ ▁DOGS 4721
4723
+ ▁SKY 4722
4724
+ ▁CULTURE 4723
4725
+ ▁PRACTICAL 4724
4726
+ ECI 4725
4727
+ 惶 4726
4728
+ 乍 4727
4729
+ ▁SIXTY 4728
4730
+ ▁PRAY 4729
4731
+ 漱 4730
4732
+ 钓 4731
4733
+ ▁COW 4732
4734
+ 兆 4733
4735
+ 啪 4734
4736
+ ▁COMPANION 4735
4737
+ 绅 4736
4738
+ ▁BAY 4737
4739
+ 践 4738
4740
+ ▁BLIND 4739
4741
+ ▁SUDDEN 4740
4742
+ ▁PRINCE 4741
4743
+ ▁MISSION 4742
4744
+ 鲤 4743
4745
+ 琅 4744
4746
+ ▁JANE 4745
4747
+ ▁FARTHER 4746
4748
+ ▁PRIZE 4747
4749
+ ▁PHYSIC 4748
4750
+ ▁LOOKED 4749
4751
+ ▁UPON 4750
4752
+ 锤 4751
4753
+ 腔 4752
4754
+ 纭 4753
4755
+ 驭 4754
4756
+ ▁THEATRE 4755
4757
+ 芝 4756
4758
+ ▁CHICAGO 4757
4759
+ ▁SIZE 4758
4760
+ 煽 4759
4761
+ 恭 4760
4762
+ ▁ANGEL 4761
4763
+ ▁GROW 4762
4764
+ 栽 4763
4765
+ ▁COMPLAIN 4764
4766
+ ▁TERR 4765
4767
+ 嗽 4766
4768
+ CTOR 4767
4769
+ ▁HORN 4768
4770
+ ILL 4769
4771
+ 吆 4770
4772
+ 刮 4771
4773
+ 畔 4772
4774
+ ▁VICTORY 4773
4775
+ ▁EIGHTEEN 4774
4776
+ 逾 4775
4777
+ ▁TUR 4776
4778
+ 戳 4777
4779
+ ▁TREASURE 4778
4780
+ ▁RABBIT 4779
4781
+ 咛 4780
4782
+ ▁BEYOND 4781
4783
+ ▁CONSIDERABLE 4782
4784
+ 憨 4783
4785
+ 仲 4784
4786
+ 谒 4785
4787
+ 邑 4786
4788
+ ▁POSSIBL 4787
4789
+ ▁ANXIOUS 4788
4790
+ 膜 4789
4791
+ 抒 4790
4792
+ 汝 4791
4793
+ 婷 4792
4794
+ 酷 4793
4795
+ 篱 4794
4796
+ 笆 4795
4797
+ 褒 4796
4798
+ 弘 4797
4799
+ IP 4798
4800
+ UNG 4799
4801
+ ▁FOREVER 4800
4802
+ 踏 4801
4803
+ ▁GROWTH 4802
4804
+ ▁ENJOYMENT 4803
4805
+ ▁VEIN 4804
4806
+ ▁KING 4805
4807
+ 熙 4806
4808
+ ▁FRESH 4807
4809
+ 颗 4808
4810
+ 仙 4809
4811
+ 伪 4810
4812
+ 姿 4811
4813
+ ▁MACHINE 4812
4814
+ ATED 4813
4815
+ 攒 4814
4816
+ 扛 4815
4817
+ 韦 4816
4818
+ 炅 4817
4819
+ REW 4818
4820
+ ▁UNREASONABL 4819
4821
+ ▁TENT 4820
4822
+ 铲 4821
4823
+ ▁CONTRIBUTE 4822
4824
+ LIE 4823
4825
+ ▁CAVE 4824
4826
+ 侄 4825
4827
+ 粥 4826
4828
+ ▁LEAP 4827
4829
+ 粮 4828
4830
+ ▁FEVER 4829
4831
+ 丘 4830
4832
+ ISM 4831
4833
+ LAND 4832
4834
+ 摒 4833
4835
+ RESS 4834
4836
+ ▁WEAPON 4835
4837
+ ▁QUESTIONS 4836
4838
+ ▁CHALLENGE 4837
4839
+ ▁CLOSELY 4838
4840
+ ▁CLOUD 4839
4841
+ ▁EVERYWHERE 4840
4842
+ ▁FLAT 4841
4843
+ ▁THINKING 4842
4844
+ ▁CONTINU 4843
4845
+ ▁JUDGE 4844
4846
+ ▁BR 4845
4847
+ ▁JAR 4846
4848
+ 缸 4847
4849
+ 谥 4848
4850
+ ▁ISSUE 4849
4851
+ 螺 4850
4852
+ 揽 4851
4853
+ 鳖 4852
4854
+ ▁INCREASED 4853
4855
+ ▁COUPLE 4854
4856
+ ▁STOVE 4855
4857
+ ▁OPPORTUNITY 4856
4858
+ 趴 4857
4859
+ ▁TOWN 4858
4860
+ ▁COTTON 4859
4861
+ ▁ENTRANCE 4860
4862
+ 蹿 4861
4863
+ 氮 4862
4864
+ ▁DANGER 4863
4865
+ ▁CONFIDENT 4864
4866
+ 洛 4865
4867
+ 杉 4866
4868
+ 矶 4867
4869
+ 淹 4868
4870
+ 滥 4869
4871
+ 椰 4870
4872
+ 薯 4871
4873
+ TLE 4872
4874
+ ▁DRANK 4873
4875
+ ITUDE 4874
4876
+ ▁AUTHOR 4875
4877
+ ▁HANDSOME 4876
4878
+ 馗 4877
4879
+ 坟 4878
4880
+ ▁INTENDED 4879
4881
+ ▁GRASS 4880
4882
+ 哆 4881
4883
+ 咪 4882
4884
+ 凶 4883
4885
+ ▁WIRE 4884
4886
+ 兑 4885
4887
+ ▁MASS 4886
4888
+ 槟 4887
4889
+ 颓 4888
4890
+ ▁THIRTEEN 4889
4891
+ ▁GENTLEMAN 4890
4892
+ 筷 4891
4893
+ ▁BRI 4892
4894
+ 爵 4893
4895
+ ERY 4894
4896
+ ▁SEATED 4895
4897
+ 闸 4896
4898
+ 刹 4897
4899
+ 裳 4898
4900
+ ▁VICTIM 4899
4901
+ ▁HURT 4900
4902
+ 滤 4901
4903
+ ▁FOOL 4902
4904
+ ▁SCARCE 4903
4905
+ 崩 4904
4906
+ 溃 4905
4907
+ ▁WAV 4906
4908
+ LAN 4907
4909
+ 郎 4908
4910
+ ▁ARGUMENT 4909
4911
+ ▁UNCERTAIN 4910
4912
+ ▁REPLIED 4911
4913
+ ▁DUST 4912
4914
+ 帘 4913
4915
+ ▁TELEGRAPH 4914
4916
+ ▁CALCULAT 4915
4917
+ ▁APART 4916
4918
+ ERSON 4917
4919
+ ▁MAR 4918
4920
+ ▁MILES 4919
4921
+ ▁INFORM 4920
4922
+ 敌 4921
4923
+ ▁IDEAS 4922
4924
+ ▁ENERGETIC 4923
4925
+ ▁SMOKE 4924
4926
+ 饶 4925
4927
+ ▁TEMPERATURE 4926
4928
+ ▁ROW 4927
4929
+ GA 4928
4930
+ 愣 4929
4931
+ 淑 4930
4932
+ ▁HASTE 4931
4933
+ ▁GREET 4932
4934
+ ▁ACCORDING 4933
4935
+ ▁REMEMBERED 4934
4936
+ 唧 4935
4937
+ 脖 4936
4938
+ ▁NECK 4937
4939
+ ▁PER 4938
4940
+ ▁TEST 4939
4941
+ OKE 4940
4942
+ 炕 4941
4943
+ 趁 4942
4944
+ 髦 4943
4945
+ ▁GENTLE 4944
4946
+ 孙 4945
4947
+ ▁DELIGHTED 4946
4948
+ ▁JENNY 4947
4949
+ 皇 4948
4950
+ 璋 4949
4951
+ ▁REMOVED 4950
4952
+ ▁PACE 4951
4953
+ 碧 4952
4954
+ 惩 4953
4955
+ 纬 4954
4956
+ 犬 4955
4957
+ ▁PIRATE 4956
4958
+ ▁FENCE 4957
4959
+ 绊 4958
4960
+ 摹 4959
4961
+ ▁REPLACE 4960
4962
+ 铵 4961
4963
+ 谜 4962
4964
+ ▁MYSTERY 4963
4965
+ ▁COLLECT 4964
4966
+ ▁MEDICINE 4965
4967
+ ▁STYLE 4966
4968
+ 忒 4967
4969
+ 沈 4968
4970
+ ▁NURSE 4969
4971
+ 薇 4970
4972
+ ▁SQUARE 4971
4973
+ 泪 4972
4974
+ 眶 4973
4975
+ 榨 4974
4976
+ UCH 4975
4977
+ ▁CLERK 4976
4978
+ ▁WILD 4977
4979
+ ▁RESERVE 4978
4980
+ ▁ROUND 4979
4981
+ ▁CANADIAN 4980
4982
+ ▁HUT 4981
4983
+ 棚 4982
4984
+ ▁ACKNOWLEDG 4983
4985
+ ▁ELEVAT 4984
4986
+ ▁RAPIDLY 4985
4987
+ ▁IMP 4986
4988
+ ▁SIGH 4987
4989
+ 晃 4988
4990
+ ▁COAL 4989
4991
+ ▁EXPIR 4990
4992
+ ▁REQUEST 4991
4993
+ ▁JAPAN 4992
4994
+ ▁KATE 4993
4995
+ ▁BAR 4994
4996
+ ▁ROUGH 4995
4997
+ ▁KNEE 4996
4998
+ ▁CHILDHOOD 4997
4999
+ 伶 4998
5000
+ 疤 4999
5001
+ 咧 5000
5002
+ ▁SATISFACTION 5001
5003
+ ▁SATISFY 5002
5004
+ ▁COMPOSITION 5003
5005
+ ▁SCORE 5004
5006
+ ▁HEAT 5005
5007
+ ▁LIST 5006
5008
+ ▁LABOUR 5007
5009
+ 捣 5008
5010
+ ▁SERV 5009
5011
+ 倩 5010
5012
+ 陕 5011
5013
+ 瓦 5012
5014
+ 坛 5013
5015
+ FORE 5014
5016
+ ▁STATE 5015
5017
+ ▁TIN 5016
5018
+ TOWN 5017
5019
+ ▁QUIETLY 5018
5020
+ ▁LEISURE 5019
5021
+ ▁ELDE 5020
5022
+ ▁SAM 5021
5023
+ 妨 5022
5024
+ ▁PRECAUTION 5023
5025
+ 慈 5024
5026
+ ▁MERCY 5025
5027
+ 俊 5026
5028
+ 雅 5027
5029
+ ▁DISCLOS 5028
5030
+ 宇 5029
5031
+ CTUALLY 5030
5032
+ 窄 5031
5033
+ ▁REFLECT 5032
5034
+ ▁GRE 5033
5035
+ ▁RAG 5034
5036
+ ▁AFTERWARDS 5035
5037
+ ▁POOL 5036
5038
+ 乙 5037
5039
+ ▁EL 5038
5040
+ 撕 5039
5041
+ 柜 5040
5042
+ ▁SEVENTEEN 5041
5043
+ 搁 5042
5044
+ ▁UNIFORM 5043
5045
+ 倪 5044
5046
+ ▁RAP 5045
5047
+ ▁TORN 5046
5048
+ 菊 5047
5049
+ 炊 5048
5050
+ ▁CONTAIN 5049
5051
+ ▁HOOK 5050
5052
+ ▁MARRIAGE 5051
5053
+ 姻 5052
5054
+ 岩 5053
5055
+ 捆 5054
5056
+ ▁SWITCH 5055
5057
+ 蓄 5056
5058
+ ▁COMFORT 5057
5059
+ 粘 5058
5060
+ 偭 5059
5061
+ ▁DRAWING 5060
5062
+ ▁QUANTIT 5061
5063
+ ▁ANGRILY 5062
5064
+ 羽 5063
5065
+ 罕 5064
5066
+ ▁FAITH 5065
5067
+ ▁DESTROYED 5066
5068
+ ▁PITY 5067
5069
+ ▁CRANE 5068
5070
+ 鹤 5069
5071
+ 赌 5070
5072
+ 笛 5071
5073
+ ▁ESSENTIAL 5072
5074
+ ▁VITAL 5073
5075
+ ▁DEBT 5074
5076
+ 泽 5075
5077
+ 辽 5076
5078
+ 婴 5077
5079
+ 嚏 5078
5080
+ ▁STORM 5079
5081
+ 缄 5080
5082
+ ▁DESERT 5081
5083
+ 陶 5082
5084
+ 醉 5083
5085
+ ▁SCREEN 5084
5086
+ 颅 5085
5087
+ 潮 5086
5088
+ ▁SEPARATE 5087
5089
+ ▁BABY 5088
5090
+ 拯 5089
5091
+ 挽 5090
5092
+ ▁SHAPE 5091
5093
+ ▁OB 5092
5094
+ 莽 5093
5095
+ 妄 5094
5096
+ 胸 5095
5097
+ 炒 5096
5098
+ 鱿 5097
5099
+ ▁OPPOSITE 5098
5100
+ 蜡 5099
5101
+ ▁WESTERN 5100
5102
+ ▁JERRY 5101
5103
+ 厄 5102
5104
+ 诊 5103
5105
+ ▁ARM 5104
5106
+ 侵 5105
5107
+ ▁SENT 5106
5108
+ ISTS 5107
5109
+ ▁COMPANIONS 5108
5110
+ ▁ATTENTIVE 5109
5111
+ ▁OBLIG 5110
5112
+ ▁UNNECESSARY 5111
5113
+ ▁ROLL 5112
5114
+ ▁PRAISE 5113
5115
+ ▁RAW 5114
5116
+ ▁HUNG 5115
5117
+ GGING 5116
5118
+ ▁FINAL 5117
5119
+ ▁CASUAL 5118
5120
+ ▁UNC 5119
5121
+ ▁FREEDOM 5120
5122
+ ▁CONVICT 5121
5123
+ ▁UNFORTUNATE 5122
5124
+ ▁CATTLE 5123
5125
+ 凤 5124
5126
+ 蘸 5125
5127
+ 酱 5126
5128
+ ▁GUILTY 5127
5129
+ 怂 5128
5130
+ ▁RAISED 5129
5131
+ ▁PURSE 5130
5132
+ ▁GRI 5131
5133
+ ▁SECURITY 5132
5134
+ GGY 5133
5135
+ ▁MIX 5134
5136
+ ▁PAINFUL 5135
5137
+ ▁POLITICIAN 5136
5138
+ ▁MOUNT 5137
5139
+ 髓 5138
5140
+ 兽 5139
5141
+ EFFICIENT 5140
5142
+ 抉 5141
5143
+ 柚 5142
5144
+ 嗐 5143
5145
+ 骂 5144
5146
+ ▁WOODS 5145
5147
+ ▁DECLARE 5146
5148
+ ▁SCALE 5147
5149
+ ▁CHAIR 5148
5150
+ SHONE 5149
5151
+ ▁PURPOSE 5150
5152
+ ▁HURRIED 5151
5153
+ ▁JACKET 5152
5154
+ ▁CHI 5153
5155
+ 辖 5154
5156
+ 诅 5155
5157
+ ▁DRUNK 5156
5158
+ 策 5157
5159
+ ▁SIGNATURE 5158
5160
+ ▁DEPART 5159
5161
+ ▁DEPARTURE 5160
5162
+ ▁TELLING 5161
5163
+ 谣 5162
5164
+ ▁PREVIOUS 5163
5165
+ ▁BATTLE 5164
5166
+ ▁DEEP 5165
5167
+ ▁IMPRESSION 5166
5168
+ MMI 5167
5169
+ ▁EXPLAINED 5168
5170
+ ▁OCCASIONALLY 5169
5171
+ ▁GRANT 5170
5172
+ ▁NORMAL 5171
5173
+ ▁CONTENT 5172
5174
+ ▁FATIGUE 5173
5175
+ ▁NEGATIVE 5174
5176
+ 押 5175
5177
+ ▁FALLEN 5176
5178
+ 愧 5177
5179
+ 吼 5178
5180
+ ▁RECORD 5179
5181
+ 燕 5180
5182
+ ▁PRISON 5181
5183
+ 郭 5182
5184
+ WARD 5183
5185
+ 漠 5184
5186
+ 蔼 5185
5187
+ ▁DESTROY 5186
5188
+ 郁 5187
5189
+ 绒 5188
5190
+ ▁BITTERLY 5189
5191
+ ▁NU 5190
5192
+ 壳 5191
5193
+ ▁ARCH 5192
5194
+ ▁FOG 5193
5195
+ 蕴 5194
5196
+ 狮 5195
5197
+ 糅 5196
5198
+ ▁IMPATIENT 5197
5199
+ ▁COMMAND 5198
5200
+ ▁SOLDIERS 5199
5201
+ 踊 5200
5202
+ ▁LENGTH 5201
5203
+ 狱 5202
5204
+ ▁CAST 5203
5205
+ 睫 5204
5206
+ 晾 5205
5207
+ ▁MILL 5206
5208
+ ▁ALOUD 5207
5209
+ 砌 5208
5210
+ ▁CARPET 5209
5211
+ ▁LITERATURE 5210
5212
+ ▁ACTION 5211
5213
+ 咕 5212
5214
+ 噜 5213
5215
+ ▁CONCLUDE 5214
5216
+ 惦 5215
5217
+ ▁GENERATION 5216
5218
+ ▁CHRISTMAS 5217
5219
+ ▁ANGLE 5218
5220
+ IO 5219
5221
+ ▁KNOWING 5220
5222
+ 亥 5221
5223
+ ▁ZE 5222
5224
+ ▁OBJECT 5223
5225
+ ▁JEFF 5224
5226
+ 坡 5225
5227
+ 魂 5226
5228
+ ▁DARLING 5227
5229
+ 贪 5228
5230
+ 婪 5229
5231
+ ▁CONSEQUENCE 5230
5232
+ ▁BLOOD 5231
5233
+ 屡 5232
5234
+ ▁SEEK 5233
5235
+ ▁YOUTH 5234
5236
+ ▁CONVINCE 5235
5237
+ 庞 5236
5238
+ ▁PROBABLE 5237
5239
+ ▁DREW 5238
5240
+ ▁DRAWN 5239
5241
+ ▁EMPTY 5240
5242
+ ▁BUCK 5241
5243
+ ▁TUNNEL 5242
5244
+ 嫉 5243
5245
+ 妒 5244
5246
+ ▁DEFEND 5245
5247
+ 豚 5246
5248
+ 怯 5247
5249
+ ▁CENTURY 5248
5250
+ 薛 5249
5251
+ 谦 5250
5252
+ ▁DECLIN 5251
5253
+ ▁MOTOR 5252
5254
+ ▁CAL 5253
5255
+ 悠 5254
5256
+ ▁PASSED 5255
5257
+ ▁NATION 5256
5258
+ 滔 5257
5259
+ 逮 5258
5260
+ 蒋 5259
5261
+ ▁CURIOUS 5260
5262
+ 秃 5261
5263
+ ▁SAYS 5262
5264
+ ▁TOTAL 5263
5265
+ ▁VAL 5264
5266
+ 曰 5265
5267
+ ▁PANIC 5266
5268
+ ▁ROOF 5267
5269
+ 翁 5268
5270
+ ▁SITTING 5269
5271
+ ▁OTHERWISE 5270
5272
+ LIKE 5271
5273
+ 黛 5272
5274
+ 绳 5273
5275
+ ▁PROFOUND 5274
5276
+ 翟 5275
5277
+ 晓 5276
5278
+ ▁POSITIVE 5277
5279
+ IFIED 5278
5280
+ 郑 5279
5281
+ 矢 5280
5282
+ ▁REMOVE 5281
5283
+ 秦 5282
5284
+ ▁RUTH 5283
5285
+ ▁SINK 5284
5286
+ ▁SINGLE 5285
5287
+ 狠 5286
5288
+ 肺 5287
5289
+ 腑 5288
5290
+ 镯 5289
5291
+ 蚊 5290
5292
+ ▁MAINTAIN 5291
5293
+ 捞 5292
5294
+ 吞 5293
5295
+ 馄 5294
5296
+ 饨 5295
5297
+ ▁LOVELY 5296
5298
+ 蹲 5297
5299
+ 遐 5298
5300
+ ▁ITALIAN 5299
5301
+ 俞 5300
5302
+ ▁ADVANC 5301
5303
+ ▁CONQUER 5302
5304
+ ▁ROAST 5303
5305
+ ▁REP 5304
5306
+ ▁SURPRISING 5305
5307
+ ▁SALT 5306
5308
+ 铭 5307
5309
+ 鞍 5308
5310
+ WELL 5309
5311
+ ▁IRON 5310
5312
+ 熨 5311
5313
+ 沓 5312
5314
+ 疏 5313
5315
+ ▁CONSTRUCT 5314
5316
+ ▁MEAL 5315
5317
+ ▁MON 5316
5318
+ ▁GHOST 5317
5319
+ ▁STRENGTH 5318
5320
+ 吴 5319
5321
+ 趟 5320
5322
+ 肠 5321
5323
+ ▁SILLY 5322
5324
+ ▁SOCIAL 5323
5325
+ ▁SETTING 5324
5326
+ 哗 5325
5327
+ ▁VINE 5326
5328
+ 馨 5327
5329
+ ▁TIP 5328
5330
+ 坪 5329
5331
+ 跤 5330
5332
+ 浑 5331
5333
+ 啵 5332
5334
+ ▁OBSERVATION 5333
5335
+ ▁TRIFL 5334
5336
+ 嫌 5335
5337
+ ▁SUPPLI 5336
5338
+ ▁CONNECTION 5337
5339
+ ▁SCU 5338
5340
+ 舟 5339
5341
+ ▁PROVINCE 5340
5342
+ 眨 5341
5343
+ ▁VIVID 5342
5344
+ 逊 5343
5345
+ ▁WANDER 5344
5346
+ ▁CITIZEN 5345
5347
+ ▁INCIDENT 5346
5348
+ ▁DELIGHTFUL 5347
5349
+ ▁RESIGN 5348
5350
+ 蘑 5349
5351
+ ▁CONDITIONS 5350
5352
+ 甭 5351
5353
+ 枣 5352
5354
+ NCH 5353
5355
+ ▁PARCEL 5354
5356
+ ▁PUZZL 5355
5357
+ 掀 5356
5358
+ ▁MASK 5357
5359
+ ▁REPAY 5358
5360
+ 旺 5359
5361
+ ▁STATEMENT 5360
5362
+ 蓉 5361
5363
+ COMING 5362
5364
+ ▁TERROR 5363
5365
+ ▁NEEDED 5364
5366
+ 拷 5365
5367
+ 碘 5366
5368
+ 眯 5367
5369
+ ▁HEDGE 5368
5370
+ ▁CONFUSED 5369
5371
+ ▁MAD 5370
5372
+ 撂 5371
5373
+ 哑 5372
5374
+ 磕 5373
5375
+ 禅 5374
5376
+ ▁FLASH 5375
5377
+ ▁INVOLVE 5376
5378
+ ▁PANT 5377
5379
+ ▁PROBABLY 5378
5380
+ 绸 5379
5381
+ 瓷 5380
5382
+ ▁AGENT 5381
5383
+ ▁INDIANS 5382
5384
+ ▁SURROUNDING 5383
5385
+ 琢 5384
5386
+ ▁MOSCOW 5385
5387
+ ▁LAID 5386
5388
+ 艇 5387
5389
+ 嗅 5388
5390
+ 撰 5389
5391
+ 锅 5390
5392
+ 奉 5391
5393
+ 斟 5392
5394
+ 酌 5393
5395
+ ▁POLITICAL 5394
5396
+ ETH 5395
5397
+ ▁RECOMMEND 5396
5398
+ 痴 5397
5399
+ ▁IMPERFECT 5398
5400
+ ▁REVEAL 5399
5401
+ 捎 5400
5402
+ ▁PEARL 5401
5403
+ OLOGICAL 5402
5404
+ 冤 5403
5405
+ 枉 5404
5406
+ ▁WORE 5405
5407
+ 氓 5406
5408
+ 蹦 5407
5409
+ ▁FAC 5408
5410
+ ▁DIFFICULTIES 5409
5411
+ 裸 5410
5412
+ ▁SHINING 5411
5413
+ 菠 5412
5414
+ ▁FLEE 5413
5415
+ FALL 5414
5416
+ 冯 5415
5417
+ WA 5416
5418
+ 肿 5417
5419
+ ▁BORDER 5418
5420
+ 哩 5419
5421
+ AVE 5420
5422
+ ▁CONSUM 5421
5423
+ 辘 5422
5424
+ ▁SIMPL 5423
5425
+ 妥 5424
5426
+ ▁POUR 5425
5427
+ 苛 5426
5428
+ 靛 5427
5429
+ 桶 5428
5430
+ 咔 5429
5431
+ 娶 5430
5432
+ 烛 5431
5433
+ ▁DELIGHT 5432
5434
+ 畏 5433
5435
+ ▁SWING 5434
5436
+ ▁HOLLOW 5435
5437
+ 昼 5436
5438
+ 患 5437
5439
+ ▁RESIST 5438
5440
+ BREAK 5439
5441
+ ▁HARVEST 5440
5442
+ 掰 5441
5443
+ ▁POWERFUL 5442
5444
+ 鞠 5443
5445
+ 躬 5444
5446
+ 湿 5445
5447
+ ▁PUTT 5446
5448
+ 鸭 5447
5449
+ ▁PRINCIPAL 5448
5450
+ ▁REAR 5449
5451
+ ▁KINGDOM 5450
5452
+ ▁MONK 5451
5453
+ ▁UPSTAIRS 5452
5454
+ ▁MISTRESS 5453
5455
+ ▁STRIP 5454
5456
+ ▁DIAMOND 5455
5457
+ 唏 5456
5458
+ 拘 5457
5459
+ ▁BON 5458
5460
+ 哀 5459
5461
+ 咸 5460
5462
+ ▁PURSU 5461
5463
+ ADE 5462
5464
+ 菌 5463
5465
+ ▁RECEIV 5464
5466
+ 霍 5465
5467
+ ▁ARRANGE 5466
5468
+ 匿 5467
5469
+ ▁HESITATING 5468
5470
+ ▁ALTOGETHER 5469
5471
+ ▁FUNERAL 5470
5472
+ ▁VAN 5471
5473
+ 嘎 5472
5474
+ ▁EXPECTED 5473
5475
+ ▁MUSCLE 5474
5476
+ CULAR 5475
5477
+ ▁SLIM 5476
5478
+ 爪 5477
5479
+ 呛 5478
5480
+ ▁HOP 5479
5481
+ ▁ACCOMPLISH 5480
5482
+ ▁PURPLE 5481
5483
+ 妆 5482
5484
+ 耕 5483
5485
+ 耘 5484
5486
+ ▁BREEZE 5485
5487
+ ▁PATTERN 5486
5488
+ 焉 5487
5489
+ 铸 5488
5490
+ ▁SIGNIFICANT 5489
5491
+ 蚂 5490
5492
+ 蚁 5491
5493
+ 桔 5492
5494
+ 杆 5493
5495
+ ▁DISAPPEAR 5494
5496
+ 儒 5495
5497
+ 炬 5496
5498
+ 嘻 5497
5499
+ ▁SMILED 5498
5500
+ ▁GUILT 5499
5501
+ 姜 5500
5502
+ ▁COMRADE 5501
5503
+ 蒂 5502
5504
+ ▁STRUCK 5503
5505
+ 膏 5504
5506
+ 塘 5505
5507
+ ▁POND 5506
5508
+ 诫 5507
5509
+ ▁BAB 5508
5510
+ 傍 5509
5511
+ ▁DUSK 5510
5512
+ 御 5511
5513
+ 梅 5512
5514
+ ▁SECRETARY 5513
5515
+ 囧 5514
5516
+ ▁AMAZED 5515
5517
+ 丞 5516
5518
+ 贾 5517
5519
+ 汀 5518
5520
+ 岂 5519
5521
+ ▁OFFICER 5520
5522
+ ▁WINDOWS 5521
5523
+ 抚 5522
5524
+ 遛 5523
5525
+ 渠 5524
5526
+ ▁BARGAIN 5525
5527
+ ▁FASCINAT 5526
5528
+ ▁PROPOSAL 5527
5529
+ ▁CHIN 5528
5530
+ ▁TEMPORARY 5529
5531
+ ▁WEALTH 5530
5532
+ 奄 5531
5533
+ ▁FEELINGS 5532
5534
+ 瞻 5533
5535
+ ▁HUNGER 5534
5536
+ ▁LOVED 5535
5537
+ 托 5536
5538
+ ▁COLLECTION 5537
5539
+ 剥 5538
5540
+ ▁MANNER 5539
5541
+ ▁FORTH 5540
5542
+ 饼 5541
5543
+ ▁PHOTOGRAPH 5542
5544
+ 闺 5543
5545
+ ▁DICTAT 5544
5546
+ ▁HENCE 5545
5547
+ 玫 5546
5548
+ 瑰 5547
5549
+ ▁CALLING 5548
5550
+ ▁GOLDEN 5549
5551
+ 肌 5550
5552
+ ▁PATIENCE 5551
5553
+ 勋 5552
5554
+ ▁MOVEMENT 5553
5555
+ ▁WISDOM 5554
5556
+ 赫 5555
5557
+ 兹 5556
5558
+ ▁CONSIDERED 5557
5559
+ ▁CR 5558
5560
+ 砥 5559
5561
+ ▁PARTS 5560
5562
+ 摞 5561
5563
+ 泥 5562
5564
+ 讯 5563
5565
+ ▁SAVED 5564
5566
+ ▁STOLE 5565
5567
+ 柠 5566
5568
+ 檬 5567
5569
+ 豌 5568
5570
+ ▁PREJUDICE 5569
5571
+ ▁APPROACH 5570
5572
+ ▁GEN 5571
5573
+ ▁RELIEV 5572
5574
+ ▁SHIPS 5573
5575
+ ▁ACCUR 5574
5576
+ 屁 5575
5577
+ 拇 5576
5578
+ 趾 5577
5579
+ ▁INJURY 5578
5580
+ LIGHT 5579
5581
+ 莓 5580
5582
+ ▁ARMS 5581
5583
+ 荫 5582
5584
+ 胁 5583
5585
+ ▁RUIN 5584
5586
+ ▁THUNDER 5585
5587
+ 逛 5586
5588
+ 吟 5587
5589
+ 粽 5588
5590
+ 敷 5589
5591
+ 骚 5590
5592
+ ▁APARTMENT 5591
5593
+ ▁RETURNED 5592
5594
+ CAL 5593
5595
+ ▁TRANSLAT 5594
5596
+ ▁SHOOT 5595
5597
+ ▁FAVOUR 5596
5598
+ 凳 5597
5599
+ ▁NET 5598
5600
+ ▁POET 5599
5601
+ 伍 5600
5602
+ ▁UNIQUE 5601
5603
+ 捍 5602
5604
+ 吱 5603
5605
+ 闷 5604
5606
+ 葛 5605
5607
+ ▁HIGHER 5606
5608
+ ▁EXPLOR 5607
5609
+ ▁APPEARANCE 5608
5610
+ ▁SKIN 5609
5611
+ 捧 5610
5612
+ ▁RASH 5611
5613
+ 橄 5612
5614
+ 榄 5613
5615
+ 毗 5614
5616
+ ▁SOLDIER 5615
5617
+ ▁CHAMPION 5616
5618
+ 哏 5617
5619
+ ▁LAP 5618
5620
+ 矣 5619
5621
+ ▁DAT 5620
5622
+ ▁FLEECE 5621
5623
+ ▁REPEAT 5622
5624
+ ▁REPUTATION 5623
5625
+ ▁CAPITAL 5624
5626
+ ▁TALE 5625
5627
+ 搏 5626
5628
+ ▁IGNORANT 5627
5629
+ ▁CHURCH 5628
5630
+ 翼 5629
5631
+ ▁RECOGNIZE 5630
5632
+ ▁LAMP 5631
5633
+ ▁LOAD 5632
5634
+ 剃 5633
5635
+ 洽 5634
5636
+ 宕 5635
5637
+ 捷 5636
5638
+ ▁FIGHTING 5637
5639
+ 庇 5638
5640
+ ▁CLASSES 5639
5641
+ 佣 5640
5642
+ ▁EMPLOY 5641
5643
+ 锚 5642
5644
+ ▁SIMILAR 5643
5645
+ ▁PROCESS 5644
5646
+ 倚 5645
5647
+ 宰 5646
5648
+ ▁PRAYER 5647
5649
+ 瞧 5648
5650
+ ▁APPROPRIATE 5649
5651
+ 荒 5650
5652
+ 掘 5651
5653
+ 蔽 5652
5654
+ 笙 5653
5655
+ 缠 5654
5656
+ ▁CLEARLY 5655
5657
+ 祭 5656
5658
+ 祀 5657
5659
+ 鹰 5658
5660
+ ▁CIRCLE 5659
5661
+ 魏 5660
5662
+ 奈 5661
5663
+ ▁IMAGINATION 5662
5664
+ 株 5663
5665
+ ▁FL 5664
5666
+ 擎 5665
5667
+ 疙 5666
5668
+ 瘩 5667
5669
+ ▁DAVID 5668
5670
+ 夯 5669
5671
+ 扼 5670
5672
+ ▁DISCOVERY 5671
5673
+ 腻 5672
5674
+ 俏 5673
5675
+ 拳 5674
5676
+ ▁GI 5675
5677
+ AFF 5676
5678
+ 掺 5677
5679
+ 阜 5678
5680
+ 辜 5679
5681
+ 疚 5680
5682
+ 陋 5681
5683
+ 镳 5682
5684
+ 煤 5683
5685
+ ▁PROMISED 5684
5686
+ ▁DRAMA 5685
5687
+ ▁SILK 5686
5688
+ 枭 5687
5689
+ 壁 5688
5690
+ ▁RUSSIAN 5689
5691
+ ▁FEET 5690
5692
+ 剑 5691
5693
+ 扳 5692
5694
+ ▁ANCESTORS 5693
5695
+ ▁EARLIE 5694
5696
+ ▁PAUSE 5695
5697
+ 跺 5696
5698
+ 羿 5697
5699
+ ▁TANK 5698
5700
+ 坊 5699
5701
+ 姥 5700
5702
+ ▁TWIG 5701
5703
+ 钎 5702
5704
+ 昌 5703
5705
+ ▁DRIVING 5704
5706
+ 萧 5705
5707
+ 瑟 5706
5708
+ ▁RELEASE 5707
5709
+ 吊 5708
5710
+ ▁UNDERSTOOD 5709
5711
+ ▁PREACH 5710
5712
+ ▁LIKED 5711
5713
+ ▁THIRST 5712
5714
+ 吏 5713
5715
+ ▁NINTH 5714
5716
+ ▁EMPEROR 5715
5717
+ ▁PARDON 5716
5718
+ 搪 5717
5719
+ 皿 5718
5720
+ ▁INSTRUCT 5719
5721
+ ▁INSTRUCTIONS 5720
5722
+ 嘀 5721
5723
+ ▁MILTON 5722
5724
+ ▁SEMI 5723
5725
+ ▁DISTRESS 5724
5726
+ ▁STEAL 5725
5727
+ 隘 5726
5728
+ 毙 5727
5729
+ 芷 5728
5730
+ ▁STAFF 5729
5731
+ ▁MISFORTUNE 5730
5732
+ ▁PRACTIS 5731
5733
+ 涩 5732
5734
+ 惭 5733
5735
+ 宙 5734
5736
+ 匆 5735
5737
+ 龈 5736
5738
+ ▁INTERRUPT 5737
5739
+ ▁JAMES 5738
5740
+ ▁DECLARATION 5739
5741
+ 雏 5740
5742
+ ▁OURSELVES 5741
5743
+ ▁IDEAL 5742
5744
+ ▁STRIKING 5743
5745
+ ▁ARTIST 5744
5746
+ 蕊 5745
5747
+ 氪 5746
5748
+ 蜷 5747
5749
+ 氰 5748
5750
+ ▁SHAME 5749
5751
+ ▁BRAND 5750
5752
+ 疆 5751
5753
+ 昔 5752
5754
+ ▁INCLINED 5753
5755
+ ▁BEGGAR 5754
5756
+ 腕 5755
5757
+ 勉 5756
5758
+ 恳 5757
5759
+ 捯 5758
5760
+ 饬 5759
5761
+ ▁ELEVEN 5760
5762
+ ▁REACHED 5761
5763
+ 颇 5762
5764
+ ▁VARIETY 5763
5765
+ ▁EMMA 5764
5766
+ ▁KICK 5765
5767
+ ▁SLIGHTLY 5766
5768
+ ▁KILLED 5767
5769
+ LICK 5768
5770
+ ▁CHARMING 5769
5771
+ 濯 5770
5772
+ ▁COVERED 5771
5773
+ COURSE 5772
5774
+ 硕 5773
5775
+ ▁EASTER 5774
5776
+ ▁CHRISTIAN 5775
5777
+ 贞 5776
5778
+ 贷 5777
5779
+ ▁REVOLUTION 5778
5780
+ ▁HILLS 5779
5781
+ ▁MOUNTAINS 5780
5782
+ ▁STATU 5781
5783
+ ▁INFORMED 5782
5784
+ ▁BELIEVED 5783
5785
+ ▁PURE 5784
5786
+ ▁GUEST 5785
5787
+ 歃 5786
5788
+ ▁TAIL 5787
5789
+ ▁SLIP 5788
5790
+ 屑 5789
5791
+ ▁TAP 5790
5792
+ ▁CANDLE 5791
5793
+ ▁BOOT 5792
5794
+ EY 5793
5795
+ 哺 5794
5796
+ VA 5795
5797
+ 拢 5796
5798
+ ▁REFORM 5797
5799
+ 昙 5798
5800
+ ▁PRINCIPLE 5799
5801
+ ▁BOIL 5800
5802
+ LAS 5801
5803
+ 葫 5802
5804
+ 芦 5803
5805
+ 顽 5804
5806
+ ▁STRUCTURE 5805
5807
+ ▁SLEPT 5806
5808
+ ▁CURTAIN 5807
5809
+ ▁CRIME 5808
5810
+ ▁SUNLIGHT 5809
5811
+ 涛 5810
5812
+ 尿 5811
5813
+ ▁IMAGIN 5812
5814
+ ▁CIVILIZATION 5813
5815
+ 睬 5814
5816
+ ▁EXACTLY 5815
5817
+ ▁GROCER 5816
5818
+ ▁DRIED 5817
5819
+ 媳 5818
5820
+ 喇 5819
5821
+ 叭 5820
5822
+ ▁TROOP 5821
5823
+ 厢 5822
5824
+ ▁STOOP 5823
5825
+ 婶 5824
5826
+ ▁FEMALE 5825
5827
+ 嗒 5826
5828
+ ▁MEMORABLE 5827
5829
+ ▁CLO 5828
5830
+ 隰 5829
5831
+ 泮 5830
5832
+ 蕾 5831
5833
+ ▁BRIEF 5832
5834
+ 姚 5833
5835
+ ▁MIDNIGHT 5834
5836
+ ▁APPRECIATION 5835
5837
+ 稻 5836
5838
+ ▁CARDINAL 5837
5839
+ ▁PARTICULARLY 5838
5840
+ 锡 5839
5841
+ 咎 5840
5842
+ 辍 5841
5843
+ FARE 5842
5844
+ ▁ERIC 5843
5845
+ 撅 5844
5846
+ ▁EIGHTH 5845
5847
+ 鑫 5846
5848
+ ▁SIMON 5847
5849
+ ▁ENTERED 5848
5850
+ 窥 5849
5851
+ 觐 5850
5852
+ 晶 5851
5853
+ 匮 5852
5854
+ 勿 5853
5855
+ 侠 5854
5856
+ ▁SEX 5855
5857
+ ▁HUM 5856
5858
+ ▁PROPOS 5857
5859
+ ▁HAPPILY 5858
5860
+ 恍 5859
5861
+ ▁DIVERS 5860
5862
+ ▁COACH 5861
5863
+ ▁YO 5862
5864
+ 昭 5863
5865
+ ▁REALITY 5864
5866
+ 蜻 5865
5867
+ 蜓 5866
5868
+ 怡 5867
5869
+ 佐 5868
5870
+ 钞 5869
5871
+ 壶 5870
5872
+ 哔 5871
5873
+ 幂 5872
5874
+ 炭 5873
5875
+ ▁FORGOTTEN 5874
5876
+ 谐 5875
5877
+ 牲 5876
5878
+ 畜 5877
5879
+ ▁CEREMONY 5878
5880
+ ▁PLATFORM 5879
5881
+ 赵 5880
5882
+ 瑕 5881
5883
+ 疵 5882
5884
+ 踹 5883
5885
+ 乳 5884
5886
+ ▁ENGAGEMENT 5885
5887
+ ▁QUO 5886
5888
+ ▁VIOLENCE 5887
5889
+ ▁RISING 5888
5890
+ ▁RAIS 5889
5891
+ ABLY 5890
5892
+ ▁ORGANIZATION 5891
5893
+ 煜 5892
5894
+ 虞 5893
5895
+ ▁PLEASED 5894
5896
+ 柬 5895
5897
+ ▁GRAIN 5896
5898
+ 履 5897
5899
+ ▁ATLANTIC 5898
5900
+ ▁CHASE 5899
5901
+ ▁FEATHER 5900
5902
+ 榴 5901
5903
+ 嘭 5902
5904
+ 晤 5903
5905
+ ▁FUNCTION 5904
5906
+ ▁INDIVIDUAL 5905
5907
+ 拱 5906
5908
+ ▁MENTION 5907
5909
+ ▁NECESSARILY 5908
5910
+ 傅 5909
5911
+ ▁INSTINCT 5910
5912
+ 谙 5911
5913
+ 寥 5912
5914
+ 袁 5913
5915
+ 肴 5914
5916
+ 贻 5915
5917
+ ▁WEDDING 5916
5918
+ 亩 5917
5919
+ 呲 5918
5920
+ 甩 5919
5921
+ 赴 5920
5922
+ 厥 5921
5923
+ 埃 5922
5924
+ ▁SHELTER 5923
5925
+ 拦 5924
5926
+ 霹 5925
5927
+ 雳 5926
5928
+ ▁INTIMATE 5927
5929
+ 惹 5928
5930
+ 鸥 5929
5931
+ WEPT 5930
5932
+ 腭 5931
5933
+ CRI 5932
5934
+ 帖 5933
5935
+ ▁CONSCIOUS 5934
5936
+ 恙 5935
5937
+ ▁PRECED 5936
5938
+ 朴 5937
5939
+ ▁BULL 5938
5940
+ 阂 5939
5941
+ ▁UNTO 5940
5942
+ ▁JOURNAL 5941
5943
+ ▁LAD 5942
5944
+ 拙 5943
5945
+ ▁INDEFINITE 5944
5946
+ ▁GLID 5945
5947
+ ▁GLOW 5946
5948
+ POST 5947
5949
+ ▁DISGUISE 5948
5950
+ 缚 5949
5951
+ 猿 5950
5952
+ 虹 5951
5953
+ ▁DESERVE 5952
5954
+ ▁MATTERS 5953
5955
+ 奢 5954
5956
+ 戮 5955
5957
+ ▁FOLD 5956
5958
+ ▁SUPPOS 5957
5959
+ ▁GENTLY 5958
5960
+ ▁GOVERN 5959
5961
+ ▁DISPLAY 5960
5962
+ ▁CENTRE 5961
5963
+ ▁DELIBERAT 5962
5964
+ 兜 5963
5965
+ 铛 5964
5966
+ ▁MORAL 5965
5967
+ ▁TIGHT 5966
5968
+ ▁SLID 5967
5969
+ 赤 5968
5970
+ ▁DESCRIPTION 5969
5971
+ WOOD 5970
5972
+ GON 5971
5973
+ ▁LOCAL 5972
5974
+ ▁ELEMENT 5973
5975
+ 秩 5974
5976
+ 乃 5975
5977
+ ▁MEMORIES 5976
5978
+ 蹩 5977
5979
+ ▁SOUGHT 5978
5980
+ 囔 5979
5981
+ 朕 5980
5982
+ 筐 5981
5983
+ JA 5982
5984
+ ▁PROMOTE 5983
5985
+ ▁INTERRUPTED 5984
5986
+ ▁CRO 5985
5987
+ 绉 5986
5988
+ ▁NAMED 5987
5989
+ ▁BEGG 5988
5990
+ ▁ABSORB 5989
5991
+ ▁DISTRACT 5990
5992
+ 邋 5991
5993
+ 遢 5992
5994
+ ▁COMMIT 5993
5995
+ SCRIBED 5994
5996
+ 呕 5995
5997
+ 臭 5996
5998
+ 曹 5997
5999
+ 琪 5998
6000
+ 泱 5999
6001
+ 狄 6000
6002
+ ▁SUCCEEDED 6001
6003
+ 宅 6002
6004
+ ▁EXTREMELY 6003
6005
+ ATIONS 6004
6006
+ 镶 6005
6007
+ 嵌 6006
6008
+ 暇 6007
6009
+ ▁TOWER 6008
6010
+ 厦 6009
6011
+ ▁GRAPE 6010
6012
+ ▁PEA 6011
6013
+ ▁OWE 6012
6014
+ ▁FLO 6013
6015
+ ▁THRILL 6014
6016
+ ▁CAPTAIN 6015
6017
+ 桑 6016
6018
+ 邃 6017
6019
+ 遣 6018
6020
+ 蹭 6019
6021
+ 吒 6020
6022
+ ▁GUARANTEE 6021
6023
+ 荧 6022
6024
+ ▁BIN 6023
6025
+ ▁BLANK 6024
6026
+ ▁STUDIO 6025
6027
+ 淳 6026
6028
+ ▁PALE 6027
6029
+ 娃 6028
6030
+ 侯 6029
6031
+ 馊 6030
6032
+ ▁CIRCUMSTANCES 6031
6033
+ MISSION 6032
6034
+ ▁IRREGULAR 6033
6035
+ ▁ENTIRELY 6034
6036
+ 迄 6035
6037
+ 脾 6036
6038
+ ▁TEMPER 6037
6039
+ ▁BARR 6038
6040
+ ▁STAMP 6039
6041
+ 税 6040
6042
+ ▁HARMONY 6041
6043
+ ▁PIPE 6042
6044
+ 茎 6043
6045
+ ▁TRAIL 6044
6046
+ ▁SLEEVE 6045
6047
+ 哞 6046
6048
+ 裘 6047
6049
+ 撩 6048
6050
+ 驻 6049
6051
+ ▁RETAIN 6050
6052
+ 岳 6051
6053
+ ▁SCIENTIFIC 6052
6054
+ 暄 6053
6055
+ ▁FACES 6054
6056
+ ▁REPEATED 6055
6057
+ ▁RAY 6056
6058
+ 栓 6057
6059
+ ▁WRIST 6058
6060
+ 竭 6059
6061
+ 诡 6060
6062
+ ▁CONTINUED 6061
6063
+ 禽 6062
6064
+ MPLE 6063
6065
+ ▁MIRROR 6064
6066
+ ▁GROOM 6065
6067
+ 悄 6066
6068
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6069
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6070
+ 瘫 6069
6071
+ 矫 6070
6072
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6073
+ 椎 6072
6074
+ 椭 6073
6075
+ 烁 6074
6076
+ ▁COMMITTEE 6075
6077
+ 桐 6076
6078
+ 醇 6077
6079
+ 汪 6078
6080
+ 祺 6079
6081
+ ▁NECESSITY 6080
6082
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6083
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6084
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6085
+ ▁REFRESH 6084
6086
+ ▁LIGHTN 6085
6087
+ ▁PATCH 6086
6088
+ ▁CORN 6087
6089
+ ▁CHARITY 6088
6090
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6091
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6092
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6093
+ ▁SHRINK 6092
6094
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6095
+ ▁MANKIND 6094
6096
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6097
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6098
+ ▁SLIPP 6097
6099
+ ▁APPOINTMENT 6098
6100
+ 腼 6099
6101
+ 腆 6100
6102
+ 扁 6101
6103
+ ▁MISTAKEN 6102
6104
+ 皙 6103
6105
+ 岐 6104
6106
+ ▁BRAZ 6105
6107
+ ▁PIT 6106
6108
+ ▁DENY 6107
6109
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6110
+ ▁FLAME 6109
6111
+ ▁ENJOYED 6110
6112
+ 朦 6111
6113
+ ▁SMILING 6112
6114
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6115
+ 硌 6114
6116
+ 彭 6115
6117
+ 晏 6116
6118
+ 敞 6117
6119
+ 烊 6118
6120
+ 弗 6119
6121
+ 潦 6120
6122
+ ▁CONSIDERATION 6121
6123
+ ▁CLIMATE 6122
6124
+ ▁RIBBON 6123
6125
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6126
+ 扒 6125
6127
+ ▁DISAPPOINTMENT 6126
6128
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6129
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6130
+ ▁HARVARD 6129
6131
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6132
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6133
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6134
+ ▁HEAP 6133
6135
+ ▁ORDINAR 6134
6136
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6137
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6138
+ 镁 6137
6139
+ ▁EDITOR 6138
6140
+ ▁BENNET 6139
6141
+ ▁TRULY 6140
6142
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6143
+ ▁CENTURIES 6142
6144
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6145
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6146
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6147
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6148
+ 仃 6147
6149
+ ▁AFFAIR 6148
6150
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6151
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6152
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6153
+ 晋 6152
6154
+ ▁DREAD 6153
6155
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6156
+ 朽 6155
6157
+ ▁PEER 6156
6158
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6159
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6160
+ 唬 6159
6161
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6162
+ ▁STONE 6161
6163
+ ▁ENDEAVOR 6162
6164
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6165
+ 讳 6164
6166
+ 夷 6165
6167
+ 薪 6166
6168
+ 萱 6167
6169
+ ▁STRAW 6168
6170
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6171
+ 绥 6170
6172
+ 幔 6171
6173
+ 喘 6172
6174
+ ▁DISCOURAG 6173
6175
+ ▁INDIAN 6174
6176
+ ▁BALLOON 6175
6177
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6178
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6179
+ ▁STREETS 6178
6180
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6181
+ 浦 6180
6182
+ ▁JULIET 6181
6183
+ 珊 6182
6184
+ 沌 6183
6185
+ 苟 6184
6186
+ 屿 6185
6187
+ 舆 6186
6188
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6189
+ ▁SURFACE 6188
6190
+ ▁RANG 6189
6191
+ ▁TERRIFI 6190
6192
+ 岗 6191
6193
+ 戚 6192
6194
+ VOLUNTARY 6193
6195
+ ▁HESITATE 6194
6196
+ 鸦 6195
6197
+ ▁EMPTI 6196
6198
+ ▁PERFUME 6197
6199
+ 葩 6198
6200
+ 匣 6199
6201
+ 毽 6200
6202
+ ▁GRAY 6201
6203
+ ▁LOSS 6202
6204
+ 霖 6203
6205
+ ▁SANK 6204
6206
+ ▁PROPOSITION 6205
6207
+ ▁RIDICULOUS 6206
6208
+ 谬 6207
6209
+ 牺 6208
6210
+ ▁EVENTS 6209
6211
+ 淮 6210
6212
+ 辟 6211
6213
+ 衩 6212
6214
+ 袍 6213
6215
+ ▁COLUMN 6214
6216
+ 穹 6215
6217
+ ▁DROWN 6216
6218
+ ▁ENGINE 6217
6219
+ 瑜 6218
6220
+ 伽 6219
6221
+ 姬 6220
6222
+ ▁LORD 6221
6223
+ ▁POSSESS 6222
6224
+ ▁CONTINENT 6223
6225
+ ▁EVIDENT 6224
6226
+ 荡 6225
6227
+ ▁GRADUALLY 6226
6228
+ 梓 6227
6229
+ 噎 6228
6230
+ ▁PRODUC 6229
6231
+ ▁BRUISE 6230
6232
+ ▁FORMER 6231
6233
+ 昧 6232
6234
+ ▁EVA 6233
6235
+ ▁BLEW 6234
6236
+ IOUS 6235
6237
+ ▁ADOPT 6236
6238
+ 媚 6237
6239
+ ▁FOLKS 6238
6240
+ 濡 6239
6241
+ 孵 6240
6242
+ ▁PRONOUNC 6241
6243
+ 侦 6242
6244
+ ▁PRIVILEGE 6243
6245
+ SGIVING 6244
6246
+ TTED 6245
6247
+ ▁THREATEN 6246
6248
+ ▁THREAT 6247
6249
+ 哧 6248
6250
+ 辉 6249
6251
+ 煌 6250
6252
+ ▁TEAR 6251
6253
+ ▁EXPEND 6252
6254
+ ▁CRIMINAL 6253
6255
+ ▁MURDER 6254
6256
+ 璐 6255
6257
+ 恕 6256
6258
+ 夭 6257
6259
+ IBLE 6258
6260
+ 聆 6259
6261
+ ▁OATH 6260
6262
+ 驰 6261
6263
+ ▁BARE 6262
6264
+ 徙 6263
6265
+ ▁LABOR 6264
6266
+ 彬 6265
6267
+ ▁SISTERS 6266
6268
+ ▁SCREAM 6267
6269
+ ▁COLLAR 6268
6270
+ 煸 6269
6271
+ ▁CREATION 6270
6272
+ 旬 6271
6273
+ ▁AROUSED 6272
6274
+ ▁ENTHUSIASM 6273
6275
+ ▁IDENTI 6274
6276
+ ▁KA 6275
6277
+ ▁RATE 6276
6278
+ ▁CRITICISM 6277
6279
+ 钝 6278
6280
+ ▁OPENING 6279
6281
+ ▁HAR 6280
6282
+ ▁CRUEL 6281
6283
+ ▁MONICA 6282
6284
+ 藉 6283
6285
+ ▁ORDERED 6284
6286
+ 叽 6285
6287
+ 喳 6286
6288
+ ▁INTERPRET 6287
6289
+ 臣 6288
6290
+ 庐 6289
6291
+ 酿 6290
6292
+ ▁CONGRATULAT 6291
6293
+ 署 6292
6294
+ 裴 6293
6295
+ 擒 6294
6296
+ 侍 6295
6297
+ 玷 6296
6298
+ 仑 6297
6299
+ 檐 6298
6300
+ ▁STUCK 6299
6301
+ ▁SHIELD 6300
6302
+ ▁JUSTICE 6301
6303
+ 飙 6302
6304
+ 缕 6303
6305
+ 嘤 6304
6306
+ 毅 6305
6307
+ 廊 6306
6308
+ ▁PROVED 6307
6309
+ ▁THOR 6308
6310
+ ▁BUTTERFLY 6309
6311
+ 岔 6310
6312
+ 隅 6311
6313
+ 鹏 6312
6314
+ 骛 6313
6315
+ 虐 6314
6316
+ 绞 6315
6317
+ 畸 6316
6318
+ ▁DISPOSED 6317
6319
+ ▁LOOSE 6318
6320
+ 噫 6319
6321
+ 豹 6320
6322
+ ▁DOMESTIC 6321
6323
+ ▁COMMENT 6322
6324
+ ▁BRIG 6323
6325
+ ▁DEFEAT 6324
6326
+ 萎 6325
6327
+ ▁ENVELOP 6326
6328
+ 霾 6327
6329
+ ▁COURT 6328
6330
+ ▁INCOME 6329
6331
+ ▁HOLDING 6330
6332
+ ▁REGION 6331
6333
+ 驳 6332
6334
+ ▁ASSIST 6333
6335
+ ▁ENTITLE 6334
6336
+ 岚 6335
6337
+ ▁ITSELF 6336
6338
+ ▁BURDEN 6337
6339
+ ▁GAINED 6338
6340
+ 撬 6339
6341
+ RANK 6340
6342
+ 黏 6341
6343
+ 稠 6342
6344
+ 唻 6343
6345
+ ▁EXCURSION 6344
6346
+ ▁GLOOMY 6345
6347
+ 鹈 6346
6348
+ 鹕 6347
6349
+ 葬 6348
6350
+ 囱 6349
6351
+ ▁FLOOD 6350
6352
+ ▁DASH 6351
6353
+ 馅 6352
6354
+ 茉 6353
6355
+ 纱 6354
6356
+ ▁WITHDRAW 6355
6357
+ 惘 6356
6358
+ ▁PROVIDED 6357
6359
+ 苔 6358
6360
+ 枢 6359
6361
+ 饸 6360
6362
+ 饹 6361
6363
+ 蝙 6362
6364
+ 蝠 6363
6365
+ ▁ACCEPTED 6364
6366
+ ▁EXTRA 6365
6367
+ ▁DISASTER 6366
6368
+ ▁EAGERLY 6367
6369
+ 喔 6368
6370
+ ▁DOORS 6369
6371
+ ▁PROFESS 6370
6372
+ ▁MONSTER 6371
6373
+ ▁DEPOSIT 6372
6374
+ ▁ASPECT 6373
6375
+ 屎 6374
6376
+ ▁FISHER 6375
6377
+ ▁DISTINCT 6376
6378
+ 舶 6377
6379
+ 咝 6378
6380
+ 桂 6379
6381
+ 佬 6380
6382
+ 犀 6381
6383
+ 亦 6382
6384
+ ▁CALIFORNIA 6383
6385
+ 來 6384
6386
+ ▁BLADE 6385
6387
+ ▁DART 6386
6388
+ 膳 6387
6389
+ ▁CHEESE 6388
6390
+ ▁STRUGGLE 6389
6391
+ ▁LAUGHED 6390
6392
+ ▁FRAME 6391
6393
+ 僧 6392
6394
+ UOUS 6393
6395
+ FOLD 6394
6396
+ 嚓 6395
6397
+ ▁SERVED 6396
6398
+ ▁ECONOMIC 6397
6399
+ ▁GOSSIP 6398
6400
+ ▁TAYLOR 6399
6401
+ 蜘 6400
6402
+ 蛛 6401
6403
+ 酝 6402
6404
+ 瞄 6403
6405
+ 殇 6404
6406
+ ▁STEEL 6405
6407
+ ▁GLANCE 6406
6408
+ 踌 6407
6409
+ 躇 6408
6410
+ 蹒 6409
6411
+ 跚 6410
6412
+ ▁RELIEF 6411
6413
+ ▁CHEEK 6412
6414
+ 颊 6413
6415
+ ▁ARRANGED 6414
6416
+ ▁WHALE 6415
6417
+ 歹 6416
6418
+ ▁EDWARD 6417
6419
+ 廉 6418
6420
+ 幢 6419
6421
+ 盔 6420
6422
+ ▁CONTRARY 6421
6423
+ 霞 6422
6424
+ ▁CONTRACT 6423
6425
+ 碾 6424
6426
+ ▁PASSION 6425
6427
+ 俐 6426
6428
+ ▁THOUGHTS 6427
6429
+ 沐 6428
6430
+ 嗟 6429
6431
+ 毋 6430
6432
+ 瘆 6431
6433
+ ▁RESEMBL 6432
6434
+ 冥 6433
6435
+ 陀 6434
6436
+ IXTURE 6435
6437
+ 伺 6436
6438
+ 霉 6437
6439
+ 锈 6438
6440
+ 踝 6439
6441
+ ▁CEASE 6440
6442
+ 芭 6441
6443
+ ▁NOBLE 6442
6444
+ ▁KNIGHT 6443
6445
+ ▁NODDED 6444
6446
+ 宵 6445
6447
+ 叛 6446
6448
+ ▁EXACT 6447
6449
+ ▁STUFF 6448
6450
+ 墟 6449
6451
+ 湣 6450
6452
+ ▁GORGE 6451
6453
+ ▁RETIRED 6452
6454
+ 澄 6453
6455
+ ▁MILITA 6454
6456
+ PIECE 6455
6457
+ ▁SOUTHERN 6456
6458
+ ▁COMMISSION 6457
6459
+ 竿 6458
6460
+ 坤 6459
6461
+ 尹 6460
6462
+ 彤 6461
6463
+ ▁LANTERN 6462
6464
+ 婊 6463
6465
+ 噩 6464
6466
+ 盹 6465
6467
+ ▁PROOF 6466
6468
+ 锹 6467
6469
+ ▁CLAIM 6468
6470
+ 董 6469
6471
+ ▁REPUBLIC 6470
6472
+ ▁WRAP 6471
6473
+ 褂 6472
6474
+ 袄 6473
6475
+ 腊 6474
6476
+ ▁CREDIT 6475
6477
+ 膛 6476
6478
+ 诌 6477
6479
+ 刃 6478
6480
+ 沏 6479
6481
+ ▁TRANSFORM 6480
6482
+ ▁TRIGGER 6481
6483
+ ▁ANNUAL 6482
6484
+ ▁GLOBE 6483
6485
+ 秉 6484
6486
+ ▁UNIVERSE 6485
6487
+ ▁DAWN 6486
6488
+ 拂 6487
6489
+ ▁SUNSET 6488
6490
+ ▁TERRIBL 6489
6491
+ 谍 6490
6492
+ ▁PITCH 6491
6493
+ 嗡 6492
6494
+ 囤 6493
6495
+ ▁CAPABLE 6494
6496
+ ▁POWDER 6495
6497
+ 乾 6496
6498
+ 龟 6497
6499
+ ▁SWIFT 6498
6500
+ 篁 6499
6501
+ 啸 6500
6502
+ 掷 6501
6503
+ ▁DEGREE 6502
6504
+ ▁MEMBERS 6503
6505
+ ▁HORIZON 6504
6506
+ 爹 6505
6507
+ ▁CREW 6506
6508
+ ▁PLOT 6507
6509
+ ▁CREATURES 6508
6510
+ ▁AMBITION 6509
6511
+ 碑 6510
6512
+ 邓 6511
6513
+ ▁PAL 6512
6514
+ ▁GUARD 6513
6515
+ 癖 6514
6516
+ 煞 6515
6517
+ ▁CAPTURE 6516
6518
+ 寺 6517
6519
+ 庙 6518
6520
+ 蝌 6519
6521
+ 蚪 6520
6522
+ 垛 6521
6523
+ 蛾 6522
6524
+ ▁RENT 6523
6525
+ 蔓 6524
6526
+ 圭 6525
6527
+ 吾 6526
6528
+ 暨 6527
6529
+ 庚 6528
6530
+ ▁DISPUTE 6529
6531
+ ▁SI 6530
6532
+ ▁SHOUTED 6531
6533
+ 馍 6532
6534
+ 悖 6533
6535
+ ▁PLAIN 6534
6536
+ ▁RACHEL 6535
6537
+ 茱 6536
6538
+ 俺 6537
6539
+ 溯 6538
6540
+ 魄 6539
6541
+ ▁ESCAPED 6540
6542
+ 梭 6541
6543
+ VILLE 6542
6544
+ ▁WENDY 6543
6545
+ ▁ASSAULT 6544
6546
+ HOOK 6545
6547
+ 溅 6546
6548
+ ▁APPEARED 6547
6549
+ 菱 6548
6550
+ ▁LIBERTY 6549
6551
+ ▁UNEQUAL 6550
6552
+ ▁LEAGUE 6551
6553
+ ▁WRAPPED 6552
6554
+ ▁PROMPT 6553
6555
+ ▁FAIRY 6554
6556
+ 篡 6555
6557
+ 锦 6556
6558
+ 羯 6557
6559
+ ▁STRU 6558
6560
+ ▁POISON 6559
6561
+ ▁FULFIL 6560
6562
+ 雎 6561
6563
+ ▁CONVEY 6562
6564
+ ▁STEPS 6563
6565
+ ▁ENVY 6564
6566
+ ▁VIRTUE 6565
6567
+ ▁BUSH 6566
6568
+ ▁NAVY 6567
6569
+ 灿 6568
6570
+ 萍 6569
6571
+ 巫 6570
6572
+ ▁POSSESSION 6571
6573
+ 瞟 6572
6574
+ ▁TRACE 6573
6575
+ ▁APOLOGY 6574
6576
+ ▁TERRACE 6575
6577
+ 啼 6576
6578
+ 轰 6577
6579
+ ▁VILLAIN 6578
6580
+ 绣 6579
6581
+ ▁VICTOR 6580
6582
+ ▁HANGING 6581
6583
+ ▁KARA 6582
6584
+ INA 6583
6585
+ ▁MERE 6584
6586
+ ▁RECOGNIZED 6585
6587
+ 嗞 6586
6588
+ 咚 6587
6589
+ ▁PICKED 6588
6590
+ ▁DAM 6589
6591
+ ▁LINK 6590
6592
+ 沫 6591
6593
+ 羁 6592
6594
+ ▁GREY 6593
6595
+ 绽 6594
6596
+ 肤 6595
6597
+ ▁ACCORDINGLY 6596
6598
+ ▁ACCORD 6597
6599
+ 狩 6598
6600
+ 蹴 6599
6601
+ 踘 6600
6602
+ 茜 6601
6603
+ ▁HARSH 6602
6604
+ ▁PLACED 6603
6605
+ ▁HIGHEST 6604
6606
+ 粪 6605
6607
+ ▁CHIEF 6606
6608
+ ▁PASSING 6607
6609
+ ▁SPITE 6608
6610
+ 轱 6609
6611
+ 茵 6610
6612
+ ▁PERFECTLY 6611
6613
+ ▁WISHED 6612
6614
+ ▁LEAN 6613
6615
+ ISTIC 6614
6616
+ ▁STOCK 6615
6617
+ 渲 6616
6618
+ ▁WILSON 6617
6619
+ ▁APPROACHING 6618
6620
+ 薅 6619
6621
+ ▁PRIEST 6620
6622
+ ▁NAKED 6621
6623
+ 缔 6622
6624
+ 侏 6623
6625
+ ▁SURROUNDED 6624
6626
+ ▁RESENT 6625
6627
+ 堪 6626
6628
+ 诈 6627
6629
+ 匪 6628
6630
+ ▁CAMPAIGN 6629
6631
+ 萌 6630
6632
+ ▁RELIGIOUS 6631
6633
+ 叼 6632
6634
+ 斐 6633
6635
+ 坝 6634
6636
+ ▁EMPHASIS 6635
6637
+ 晗 6636
6638
+ 尸 6637
6639
+ 慵 6638
6640
+ ▁PRODUCED 6639
6641
+ ▁ESTIMATE 6640
6642
+ ▁GLORY 6641
6643
+ 氟 6642
6644
+ 溴 6643
6645
+ ▁ROUT 6644
6646
+ 瞒 6645
6647
+ 枫 6646
6648
+ 悍 6647
6649
+ 缴 6648
6650
+ ▁JEALOUS 6649
6651
+ ▁BEAST 6650
6652
+ ▁HARBOUR 6651
6653
+ 铀 6652
6654
+ ▁SUBMIT 6653
6655
+ 鸵 6654
6656
+ 肘 6655
6657
+ 蹄 6656
6658
+ ▁EGYPT 6657
6659
+ ▁IMITAT 6658
6660
+ ▁SOAP 6659
6661
+ 俭 6660
6662
+ ▁PLEASING 6661
6663
+ ▁URGE 6662
6664
+ 贮 6663
6665
+ ▁PLEDGE 6664
6666
+ HOUSE 6665
6667
+ ▁ARCHITECTUR 6666
6668
+ 撵 6667
6669
+ 拧 6668
6670
+ 槛 6669
6671
+ ▁VAIN 6670
6672
+ ▁CREATURE 6671
6673
+ 沾 6672
6674
+ ▁DEBATE 6673
6675
+ ▁POCKET 6674
6676
+ ▁BARK 6675
6677
+ ▁ROUSE 6676
6678
+ 瘪 6677
6679
+ ▁THIRTIETH 6678
6680
+ ▁ADMITTED 6679
6681
+ ▁REPRESENT 6680
6682
+ ▁BEHAVIOUR 6681
6683
+ 錒 6682
6684
+ DDING 6683
6685
+ ▁REMOTE 6684
6686
+ ▁SHAKING 6685
6687
+ ▁COMPLICAT 6686
6688
+ ▁CONSEQUENTLY 6687
6689
+ 馁 6688
6690
+ ▁WOLVES 6689
6691
+ 喋 6690
6692
+ ▁SEIZE 6691
6693
+ 磴 6692
6694
+ 撸 6693
6695
+ NLEA 6694
6696
+ 唆 6695
6697
+ ▁BRENDA 6696
6698
+ 缪 6697
6699
+ 螃 6698
6700
+ 蟹 6699
6701
+ ▁ENDEAVOUR 6700
6702
+ 耿 6701
6703
+ ▁JESUS 6702
6704
+ FOOT 6703
6705
+ 臊 6704
6706
+ 阀 6705
6707
+ ▁SERVANT 6706
6708
+ ▁DROPPED 6707
6709
+ ▁TURKEY 6708
6710
+ ▁THOU 6709
6711
+ 靡 6710
6712
+ 狰 6711
6713
+ 狞 6712
6714
+ 霜 6713
6715
+ ▁SCRATCH 6714
6716
+ 寮 6715
6717
+ ▁OBSTACLE 6716
6718
+ ▁REVENGE 6717
6719
+ 躯 6718
6720
+ ▁SCORN 6719
6721
+ 樊 6720
6722
+ ▁PROCEED 6721
6723
+ ▁TUNE 6722
6724
+ 栈 6723
6725
+ 驮 6724
6726
+ 臧 6725
6727
+ 睦 6726
6728
+ 窝 6727
6729
+ ▁IMPRISON 6728
6730
+ 赅 6729
6731
+ 肇 6730
6732
+ ▁STRUGGLING 6731
6733
+ 烽 6732
6734
+ 垢 6733
6735
+ 荔 6734
6736
+ ▁INTELLECTUAL 6735
6737
+ 熔 6736
6738
+ ▁SENSIBLE 6737
6739
+ 禧 6738
6740
+ 楂 6739
6741
+ 琦 6740
6742
+ 瓣 6741
6743
+ ▁CHRIST 6742
6744
+ ▁AFFECT 6743
6745
+ ▁SHADOW 6744
6746
+ 巅 6745
6747
+ ▁ATMOSPHERE 6746
6748
+ 肝 6747
6749
+ 凄 6748
6750
+ 枕 6749
6751
+ 焖 6750
6752
+ ▁DECENT 6751
6753
+ 雀 6752
6754
+ 阡 6753
6755
+ ▁RUSSIA 6754
6756
+ 邹 6755
6757
+ 擤 6756
6758
+ 涕 6757
6759
+ 奸 6758
6760
+ 肋 6759
6761
+ 俚 6760
6762
+ 鲲 6761
6763
+ ▁CABINET 6762
6764
+ ▁HAZARD 6763
6765
+ ▁MOONLIGHT 6764
6766
+ ▁INSPECT 6765
6767
+ 帧 6766
6768
+ ▁INSTANTLY 6767
6769
+ ▁DIRECTLY 6768
6770
+ 糗 6769
6771
+ 猥 6770
6772
+ ▁WOUNDED 6771
6773
+ 耸 6772
6774
+ 濛 6773
6775
+ 肆 6774
6776
+ ▁EQUALITY 6775
6777
+ 咩 6776
6778
+ ▁DUTIES 6777
6779
+ 炯 6778
6780
+ ▁GOODNESS 6779
6781
+ ▁ATTENDANT 6780
6782
+ 嚎 6781
6783
+ 啕 6782
6784
+ ▁GENUINE 6783
6785
+ ▁ELEGANT 6784
6786
+ ▁APPROV 6785
6787
+ ▁VISION 6786
6788
+ ▁EDGE 6787
6789
+ 恬 6788
6790
+ 刨 6789
6791
+ ▁PORTION 6790
6792
+ 蛰 6791
6793
+ ▁MISUNDERSTAND 6792
6794
+ ▁SAKE 6793
6795
+ 灶 6794
6796
+ ▁SWEAR 6795
6797
+ 鞭 6796
6798
+ 蛟 6797
6799
+ ▁PACIFIC 6798
6800
+ ▁DESTRUCTION 6799
6801
+ ▁UNWILLING 6800
6802
+ ▁SPIRITS 6801
6803
+ ▁FORMED 6802
6804
+ ▁DEFINITE 6803
6805
+ 抨 6804
6806
+ 戈 6805
6807
+ 疮 6806
6808
+ ▁ASSUME 6807
6809
+ 舰 6808
6810
+ IZZ 6809
6811
+ 涮 6810
6812
+ ▁NAVIGAT 6811
6813
+ ▁ENGAGED 6812
6814
+ 柄 6813
6815
+ ▁CAROL 6814
6816
+ 韬 6815
6817
+ ▁EXCEEDINGLY 6816
6818
+ ▁OBSERV 6817
6819
+ ▁CHILL 6818
6820
+ 蔷 6819
6821
+ 酵 6820
6822
+ 骥 6821
6823
+ 诠 6822
6824
+ 浒 6823
6825
+ 楞 6824
6826
+ 梵 6825
6827
+ ▁KNIT 6826
6828
+ 掳 6827
6829
+ 洼 6828
6830
+ 掖 6829
6831
+ 梢 6830
6832
+ 盏 6831
6833
+ 绰 6832
6834
+ ▁INDICAT 6833
6835
+ ▁RUM 6834
6836
+ 褶 6835
6837
+ ▁MOREOVER 6836
6838
+ ▁ADJUST 6837
6839
+ ▁SHOULDERS 6838
6840
+ 漉 6839
6841
+ 枚 6840
6842
+ 仕 6841
6843
+ ▁ACCESS 6842
6844
+ 棺 6843
6845
+ ▁SLAP 6844
6846
+ ▁INTENSE 6845
6847
+ 钉 6846
6848
+ 泻 6847
6849
+ 茴 6848
6850
+ 镖 6849
6851
+ 靶 6850
6852
+ 陨 6851
6853
+ ▁VIOLENT 6852
6854
+ ▁DISTANT 6853
6855
+ 泌 6854
6856
+ 汴 6855
6857
+ ▁HUNTING 6856
6858
+ ZA 6857
6859
+ ▁WILLIAM 6858
6860
+ 岭 6859
6861
+ 倔 6860
6862
+ ▁CHEST 6861
6863
+ ▁PATTY 6862
6864
+ ▁COMMITTED 6863
6865
+ 汞 6864
6866
+ ▁HUMOUR 6865
6867
+ 呣 6866
6868
+ 悯 6867
6869
+ ▁PETITION 6868
6870
+ 眺 6869
6871
+ 瞰 6870
6872
+ ▁PEAK 6871
6873
+ ▁ANKLE 6872
6874
+ ▁GENEROUS 6873
6875
+ ▁AWAIT 6874
6876
+ ▁BRILLIANT 6875
6877
+ ▁TEMPLE 6876
6878
+ ▁CHARLES 6877
6879
+ ▁SLIGHT 6878
6880
+ 籁 6879
6881
+ 婵 6880
6882
+ 娟 6881
6883
+ 缈 6882
6884
+ 沧 6883
6885
+ 溟 6884
6886
+ 傀 6885
6887
+ 儡 6886
6888
+ 嘈 6887
6889
+ 忳 6888
6890
+ 侘 6889
6891
+ 傺 6890
6892
+ SHIRE 6891
6893
+ 郡 6892
6894
+ 喵 6893
6895
+ ▁WITHIN 6894
6896
+ ▁MOMENTS 6895
6897
+ ▁BOLD 6896
6898
+ ▁PROVISION 6897
6899
+ ▁OPPOSITION 6898
6900
+ 渎 6899
6901
+ ▁WICKED 6900
6902
+ ▁VETERAN 6901
6903
+ 梧 6902
6904
+ 甄 6903
6905
+ 鸿 6904
6906
+ 鹄 6905
6907
+ ▁INQUIRY 6906
6908
+ ▁SUBSTANCE 6907
6909
+ 骼 6908
6910
+ ▁DESPERATE 6909
6911
+ ▁IMAGINED 6910
6912
+ ▁WINNING 6911
6913
+ BERRIES 6912
6914
+ 淌 6913
6915
+ ▁FAREWELL 6914
6916
+ ▁RIVAL 6915
6917
+ 泞 6916
6918
+ ▁FROG 6917
6919
+ ▁MILE 6918
6920
+ ▁EDITION 6919
6921
+ ▁FERTIL 6920
6922
+ 榷 6921
6923
+ ▁STEADY 6922
6924
+ 鹦 6923
6925
+ 鹉 6924
6926
+ ▁WAG 6925
6927
+ ▁ANNE 6926
6928
+ ▁JUDGMENT 6927
6929
+ ▁EXHIBIT 6928
6930
+ 瑶 6929
6931
+ ▁COMPREHEND 6930
6932
+ ▁PROPERTY 6931
6933
+ 娴 6932
6934
+ 罹 6933
6935
+ GGED 6934
6936
+ ▁FROWN 6935
6937
+ ▁DISTINGUISH 6936
6938
+ ▁AFFAIRS 6937
6939
+ ▁SQUIRREL 6938
6940
+ 桨 6939
6941
+ ▁ESTABLISH 6940
6942
+ 溢 6941
6943
+ 唷 6942
6944
+ ▁LACE 6943
6945
+ 怔 6944
6946
+ ▁STAIRS 6945
6947
+ 忱 6946
6948
+ ▁DOUBTFUL 6947
6949
+ ▁ABUSE 6948
6950
+ 肽 6949
6951
+ 脊 6950
6952
+ 侬 6951
6953
+ 妾 6952
6954
+ 瞩 6953
6955
+ ▁DISPATCH 6954
6956
+ 臀 6955
6957
+ ▁JEWEL 6956
6958
+ ▁PURSUIT 6957
6959
+ 絮 6958
6960
+ 蠕 6959
6961
+ 讷 6960
6962
+ ▁SPAIN 6961
6963
+ 碴 6962
6964
+ 蒜 6963
6965
+ ▁ATTRIBUT 6964
6966
+ 禾 6965
6967
+ ▁DAMP 6966
6968
+ ▁LINES 6967
6969
+ ▁BANNER 6968
6970
+ ▁SHADE 6969
6971
+ 佘 6970
6972
+ ▁MAID 6971
6973
+ 唾 6972
6974
+ ▁OBJECTION 6973
6975
+ 尉 6974
6976
+ 膘 6975
6977
+ ▁BLOSSOM 6976
6978
+ ▁HONOUR 6977
6979
+ 矜 6978
6980
+ 蒿 6979
6981
+ 泵 6980
6982
+ 窒 6981
6983
+ ▁SL 6982
6984
+ 蓬 6983
6985
+ 孚 6984
6986
+ ▁REQUIRED 6985
6987
+ ▁COLUMB 6986
6988
+ 崛 6987
6989
+ ▁FURNISH 6988
6990
+ ▁SLAVE 6989
6991
+ 裔 6990
6992
+ ▁WRECK 6991
6993
+ 懦 6992
6994
+ ▁SITUATED 6993
6995
+ 妲 6994
6996
+ ▁COMPLEX 6995
6997
+ 巡 6996
6998
+ 挞 6997
6999
+ 勘 6998
7000
+ 沼 6999
7001
+ 汲 7000
7002
+ FIELD 7001
7003
+ ▁MARVEL 7002
7004
+ 苇 7003
7005
+ 韧 7004
7006
+ ▁SEVERE 7005
7007
+ ▁DRAG 7006
7008
+ ▁CHALK 7007
7009
+ 剌 7008
7010
+ ▁POPULACE 7009
7011
+ ▁SCATTERED 7010
7012
+ 诧 7011
7013
+ ▁PRETTI 7012
7014
+ 凿 7013
7015
+ ▁PEASANT 7014
7016
+ ▁BREAST 7015
7017
+ 忐 7016
7018
+ 忑 7017
7019
+ ▁BETRAY 7018
7020
+ 汹 7019
7021
+ ▁LAWS 7020
7022
+ ▁DARKNESS 7021
7023
+ 缮 7022
7024
+ ▁HOLLAND 7023
7025
+ 栗 7024
7026
+ 瓤 7025
7027
+ ▁STRING 7026
7028
+ ▁KEEN 7027
7029
+ 妓 7028
7030
+ 宛 7029
7031
+ BI 7030
7032
+ 翠 7031
7033
+ 灸 7032
7034
+ ▁CIRCUS 7033
7035
+ ▁CASTLE 7034
7036
+ ▁PLUCK 7035
7037
+ 崭 7036
7038
+ 嫖 7037
7039
+ 戊 7038
7040
+ 戌 7039
7041
+ ▁STEER 7040
7042
+ 蹬 7041
7043
+ ▁LUXURY 7042
7044
+ UFF 7043
7045
+ 橱 7044
7046
+ 舵 7045
7047
+ ▁FIERCE 7046
7048
+ 肾 7047
7049
+ 擂 7048
7050
+ ▁FIXED 7049
7051
+ 嗤 7050
7052
+ OBIL 7051
7053
+ 孝 7052
7054
+ ▁OBSERVED 7053
7055
+ 锃 7054
7056
+ 謝 7055
7057
+ ▁ODD 7056
7058
+ ▁SAINT 7057
7059
+ 赁 7058
7060
+ ▁BITTER 7059
7061
+ 堤 7060
7062
+ 昵 7061
7063
+ ▁SAVAGE 7062
7064
+ 琥 7063
7065
+ 珀 7064
7066
+ ▁SOMEWHAT 7065
7067
+ ▁CHAIN 7066
7068
+ ▁LOSING 7067
7069
+ 咣 7068
7070
+ ▁PHI 7069
7071
+ ▁ACCUSTOM 7070
7072
+ 颤 7071
7073
+ 迂 7072
7074
+ ▁PROFESSION 7073
7075
+ ▁SUGGESTED 7074
7076
+ ▁ENTERPRISE 7075
7077
+ 腺 7076
7078
+ 嫂 7077
7079
+ ▁LUXURI 7078
7080
+ ▁CURL 7079
7081
+ ▁REGULAT 7080
7082
+ ▁PILLOW 7081
7083
+ 吕 7082
7084
+ 拴 7083
7085
+ 彦 7084
7086
+ 蜚 7085
7087
+ ▁FANCY 7086
7088
+ 掂 7087
7089
+ ▁STEPHEN 7088
7090
+ 喱 7089
7091
+ ▁UNEASY 7090
7092
+ 臃 7091
7093
+ 券 7092
7094
+ 陡 7093
7095
+ 峭 7094
7096
+ ▁RIDGE 7095
7097
+ ▁OWL 7096
7098
+ ▁MERCHANT 7097
7099
+ ▁THROWN 7098
7100
+ 珂 7099
7101
+ ▁DUN 7100
7102
+ ▁KNEES 7101
7103
+ 捅 7102
7104
+ 悚 7103
7105
+ ▁FLOUR 7104
7106
+ 呱 7105
7107
+ 砝 7106
7108
+ ▁FLORENCE 7107
7109
+ 虾 7108
7110
+ 嘣 7109
7111
+ ▁SPLENDID 7110
7112
+ ▁ABUNDANT 7111
7113
+ 窜 7112
7114
+ ▁TEAPOT 7113
7115
+ RREL 7114
7116
+ 酋 7115
7117
+ 沪 7116
7118
+ ▁ACTUAL 7117
7119
+ 砰 7118
7120
+ ▁PANEL 7119
7121
+ 衅 7120
7122
+ 诬 7121
7123
+ 蔑 7122
7124
+ ▁SWELL 7123
7125
+ 霓 7124
7126
+ 钧 7125
7127
+ 丛 7126
7128
+ ▁PEEP 7127
7129
+ 酗 7128
7130
+ ▁INTENT 7129
7131
+ ▁BENT 7130
7132
+ 藻 7131
7133
+ ▁EXTENT 7132
7134
+ ▁PSYCHOLOG 7133
7135
+ ▁WEEP 7134
7136
+ 猝 7135
7137
+ ▁GASP 7136
7138
+ 侈 7137
7139
+ 袒 7138
7140
+ ▁CREEK 7139
7141
+ 腮 7140
7142
+ ▁ABNORMAL 7141
7143
+ ▁LATIN 7142
7144
+ ▁FIST 7143
7145
+ 茸 7144
7146
+ ▁CONSCIENCE 7145
7147
+ 笃 7146
7148
+ ▁COLLINS 7147
7149
+ 瘟 7148
7150
+ 疟 7149
7151
+ 瘸 7150
7152
+ ▁GAY 7151
7153
+ 玺 7152
7154
+ 雁 7153
7155
+ 茅 7154
7156
+ 籽 7155
7157
+ ▁AID 7156
7158
+ ▁MONTE 7157
7159
+ 胯 7158
7160
+ ▁ROBE 7159
7161
+ 喏 7160
7162
+ 彰 7161
7163
+ 礴 7162
7164
+ ▁ARREST 7163
7165
+ ▁PHYSICIAN 7164
7166
+ ▁PRISONER 7165
7167
+ 犟 7166
7168
+ ▁NEARER 7167
7169
+ 谝 7168
7170
+ ▁MAL 7169
7171
+ ▁SUPPRESS 7170
7172
+ 唰 7171
7173
+ ▁INFINITE 7172
7174
+ 怠 7173
7175
+ 苞 7174
7176
+ 骸 7175
7177
+ ▁INDIFFERENT 7176
7178
+ 赎 7177
7179
+ ▁FLESH 7178
7180
+ ▁ASSISTANCE 7179
7181
+ 剁 7180
7182
+ 馒 7181
7183
+ 葵 7182
7184
+ ▁BLOOM 7183
7185
+ 觅 7184
7186
+ 噌 7185
7187
+ ▁SEPARATED 7186
7188
+ 肮 7187
7189
+ MOUTH 7188
7190
+ ▁THUMB 7189
7191
+ ▁EXPAND 7190
7192
+ 冉 7191
7193
+ 驷 7192
7194
+ ▁MESSENGER 7193
7195
+ ▁REIGN 7194
7196
+ ▁VARI 7195
7197
+ ▁OFFICERS 7196
7198
+ 翱 7197
7199
+ 槌 7198
7200
+ 暼 7199
7201
+ ▁WALLACE 7200
7202
+ 泯 7201
7203
+ 赡 7202
7204
+ ▁SURGEON 7203
7205
+ ▁DISGUST 7204
7206
+ ▁STUMP 7205
7207
+ 琼 7206
7208
+ BBL 7207
7209
+ ▁SEXUAL 7208
7210
+ ▁NUMEROUS 7209
7211
+ ▁VAST 7210
7212
+ ▁LITERA 7211
7213
+ 锌 7212
7214
+ 痪 7213
7215
+ ▁BARREL 7214
7216
+ ▁COMPLIMENT 7215
7217
+ 奕 7216
7218
+ 恺 7217
7219
+ ▁BINGLEY 7218
7220
+ ▁REMARKABLE 7219
7221
+ ▁CHAP 7220
7222
+ 旭 7221
7223
+ ▁CORDIAL 7222
7224
+ 飓 7223
7225
+ 跪 7224
7226
+ 惚 7225
7227
+ 壹 7226
7228
+ 嬛 7227
7229
+ 磊 7228
7230
+ ▁FANNY 7229
7231
+ ▁SYMPATHY 7230
7232
+ ▁APPROACHED 7231
7233
+ 怵 7232
7234
+ ▁INSTANT 7233
7235
+ 箫 7234
7236
+ ▁GENIUS 7235
7237
+ 窠 7236
7238
+ 臼 7237
7239
+ ▁GLACIER 7238
7240
+ ▁EXAMINE 7239
7241
+ ▁IMPROVEMENT 7240
7242
+ 沛 7241
7243
+ 昱 7242
7244
+ ▁ANNIE 7243
7245
+ 跋 7244
7246
+ 嗜 7245
7247
+ ▁TENDENC 7246
7248
+ 焕 7247
7249
+ ▁ADVERTISING 7248
7250
+ ▁ROTTEN 7249
7251
+ ▁FRANCIS 7250
7252
+ 扽 7251
7253
+ 枷 7252
7254
+ ▁PERSIST 7253
7255
+ ▁CRIES 7254
7256
+ ▁FIELDS 7255
7257
+ 缭 7256
7258
+ 咄 7257
7259
+ 驯 7258
7260
+ ▁CONGRESS 7259
7261
+ 糯 7260
7262
+ MONT 7261
7263
+ ▁BISCUIT 7262
7264
+ 莲 7263
7265
+ ▁BARRIER 7264
7266
+ 簿 7265
7267
+ 澎 7266
7268
+ 湃 7267
7269
+ 澜 7268
7270
+ MMED 7269
7271
+ 咿 7270
7272
+ ▁STREAK 7271
7273
+ ▁EARNEST 7272
7274
+ 蹊 7273
7275
+ ▁RUST 7274
7276
+ 缥 7275
7277
+ 熏 7276
7278
+ 痘 7277
7279
+ 潇 7278
7280
+ 帚 7279
7281
+ ▁DECK 7280
7282
+ 酣 7281
7283
+ ▁QUALITIES 7282
7284
+ ▁TERRITORY 7283
7285
+ WASH 7284
7286
+ 惆 7285
7287
+ 怅 7286
7288
+ 咏 7287
7289
+ ▁LUNGS 7288
7290
+ ▁LOFT 7289
7291
+ ▁NEIGHBOUR 7290
7292
+ 莺 7291
7293
+ ▁PARTICULAR 7292
7294
+ ▁POLISH 7293
7295
+ ▁EXTREME 7294
7296
+ ▁CONFLICT 7295
7297
+ 蔗 7296
7298
+ 拄 7297
7299
+ ▁BENEATH 7298
7300
+ 娅 7299
7301
+ 迦 7300
7302
+ ▁FEATURES 7301
7303
+ ▁RAFT 7302
7304
+ 筏 7303
7305
+ 崔 7304
7306
+ 孪 7305
7307
+ 攥 7306
7308
+ ▁EMERG 7307
7309
+ 膈 7308
7310
+ 霆 7309
7311
+ 嘁 7310
7312
+ ▁ERROR 7311
7313
+ ▁BUNCH 7312
7314
+ ▁HORRIBL 7313
7315
+ ▁DIM 7314
7316
+ ▁THREAD 7315
7317
+ ▁REVELATION 7316
7318
+ 瀚 7317
7319
+ 鲫 7318
7320
+ ▁SUSPECT 7319
7321
+ 渥 7320
7322
+ 冀 7321
7323
+ 戾 7322
7324
+ 芍 7323
7325
+ 沽 7324
7326
+ 恿 7325
7327
+ ▁EXCEED 7326
7328
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log/fast_beam_search/errs-dev-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8.txt ADDED
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log/fast_beam_search/errs-test-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8-use-averaged-model.txt ADDED
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log/fast_beam_search/errs-test-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8.txt ADDED
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log/fast_beam_search/errs-test-beam_4_max_contexts_4_max_states_8-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8.txt ADDED
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log/fast_beam_search/log-decode-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8-2022-06-22-14-29-34 ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 2022-06-22 14:29:34,905 INFO [decode.py:531] Decoding started
2
+ 2022-06-22 14:29:34,906 INFO [decode.py:537] Device: cuda:0
3
+ 2022-06-22 14:29:35,083 INFO [lexicon.py:176] Loading pre-compiled data/lang_char/Linv.pt
4
+ 2022-06-22 14:29:35,109 INFO [decode.py:547] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 50, 'reset_interval': 100, 'valid_interval': 2000, 'feature_dim': 80, 'subsampling_factor': 4, 'model_warm_step': 1000, 'env_info': {'k2-version': '1.15.1', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f8d2dba06c000ffee36aab5b66f24e7c9809f116', 'k2-git-date': 'Thu Apr 21 12:20:34 2022', 'lhotse-version': '1.4.0.dev+git.94e9ed9.clean', 'torch-version': '1.11.0', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'pruned-rnnt5-recipe-for-tal-csasr', 'icefall-git-sha1': 'c1c893b-dirty', 'icefall-git-date': 'Thu Jun 16 19:19:00 2022', 'icefall-path': '/ceph-meixu/luomingshuang/icefall', 'k2-path': '/ceph-ms/luomingshuang/k2_latest/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-meixu/luomingshuang/anaconda3/envs/k2-python/lib/python3.8/site-packages/lhotse-1.4.0.dev0+git.94e9ed9.clean-py3.8.egg/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-6-0603111709-76b8f59588-flzgf', 'IP address': '10.177.28.73'}, 'epoch': 30, 'iter': 0, 'avg': 24, 'use_averaged_model': False, 'exp_dir': PosixPath('pruned_transducer_stateless5/exp'), 'lang_dir': 'data/lang_char', 'decoding_method': 'fast_beam_search', 'beam_size': 4, 'beam': 4, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'num_encoder_layers': 24, 'dim_feedforward': 1536, 'nhead': 8, 'encoder_dim': 384, 'decoder_dim': 512, 'joiner_dim': 512, 'manifest_dir': PosixPath('data/fbank_new'), 'max_duration': 1500, 'bucketing_sampler': True, 'num_buckets': 300, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'input_strategy': 'PrecomputedFeatures', 'res_dir': PosixPath('pruned_transducer_stateless5/exp/fast_beam_search'), 'suffix': 'epoch-30-avg-24-beam-4-max-contexts-4-max-states-8', 'blank_id': 0, 'vocab_size': 7341}
5
+ 2022-06-22 14:29:35,109 INFO [decode.py:549] About to create model
6
+ 2022-06-22 14:29:35,899 INFO [decode.py:578] averaging ['pruned_transducer_stateless5/exp/epoch-7.pt', 'pruned_transducer_stateless5/exp/epoch-8.pt', 'pruned_transducer_stateless5/exp/epoch-9.pt', 'pruned_transducer_stateless5/exp/epoch-10.pt', 'pruned_transducer_stateless5/exp/epoch-11.pt', 'pruned_transducer_stateless5/exp/epoch-12.pt', 'pruned_transducer_stateless5/exp/epoch-13.pt', 'pruned_transducer_stateless5/exp/epoch-14.pt', 'pruned_transducer_stateless5/exp/epoch-15.pt', 'pruned_transducer_stateless5/exp/epoch-16.pt', 'pruned_transducer_stateless5/exp/epoch-17.pt', 'pruned_transducer_stateless5/exp/epoch-18.pt', 'pruned_transducer_stateless5/exp/epoch-19.pt', 'pruned_transducer_stateless5/exp/epoch-20.pt', 'pruned_transducer_stateless5/exp/epoch-21.pt', 'pruned_transducer_stateless5/exp/epoch-22.pt', 'pruned_transducer_stateless5/exp/epoch-23.pt', 'pruned_transducer_stateless5/exp/epoch-24.pt', 'pruned_transducer_stateless5/exp/epoch-25.pt', 'pruned_transducer_stateless5/exp/epoch-26.pt', 'pruned_transducer_stateless5/exp/epoch-27.pt', 'pruned_transducer_stateless5/exp/epoch-28.pt', 'pruned_transducer_stateless5/exp/epoch-29.pt', 'pruned_transducer_stateless5/exp/epoch-30.pt']
7
+ 2022-06-22 14:31:24,813 INFO [decode.py:638] Number of model parameters: 102139163
8
+ 2022-06-22 14:31:24,813 INFO [asr_datamodule.py:425] About to get dev cuts
9
+ 2022-06-22 14:31:24,820 INFO [asr_datamodule.py:360] About to create dev dataset
10
+ 2022-06-22 14:31:25,362 INFO [asr_datamodule.py:381] About to create dev dataloader
11
+ 2022-06-22 14:31:25,362 INFO [asr_datamodule.py:432] About to get test cuts
12
+ 2022-06-22 14:31:26,437 INFO [asr_datamodule.py:407] About to create test dataloader
13
+ 2022-06-22 14:31:31,598 INFO [decode.py:442] batch 0/?, cuts processed until now is 146
14
+ 2022-06-22 14:32:19,708 INFO [decode.py:459] The transcripts are stored in pruned_transducer_stateless5/exp/fast_beam_search/recogs-dev-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8.txt
15
+ 2022-06-22 14:32:20,059 INFO [utils.py:408] [dev-beam_4_max_contexts_4_max_states_8] %WER 5.09% [11208 / 220284, 2592 ins, 3259 del, 5357 sub ]
16
+ 2022-06-22 14:32:21,222 INFO [decode.py:472] Wrote detailed error stats to pruned_transducer_stateless5/exp/fast_beam_search/errs-dev-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8.txt
17
+ 2022-06-22 14:32:21,223 INFO [decode.py:489]
18
+ For dev, WER of different settings are:
19
+ beam_4_max_contexts_4_max_states_8 5.09 best for dev
20
+
21
+ 2022-06-22 14:32:26,025 INFO [decode.py:442] batch 0/?, cuts processed until now is 152
22
+ 2022-06-22 14:33:22,564 INFO [decode.py:442] batch 20/?, cuts processed until now is 4452
23
+ 2022-06-22 14:34:13,256 INFO [decode.py:442] batch 40/?, cuts processed until now is 9633
24
+ 2022-06-22 14:34:55,978 INFO [decode.py:459] The transcripts are stored in pruned_transducer_stateless5/exp/fast_beam_search/recogs-test-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8.txt
25
+ 2022-06-22 14:34:57,120 INFO [utils.py:408] [test-beam_4_max_contexts_4_max_states_8] %WER 5.17% [33573 / 648871, 7503 ins, 10112 del, 15958 sub ]
26
+ 2022-06-22 14:35:00,352 INFO [decode.py:472] Wrote detailed error stats to pruned_transducer_stateless5/exp/fast_beam_search/errs-test-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8.txt
27
+ 2022-06-22 14:35:00,353 INFO [decode.py:489]
28
+ For test, WER of different settings are:
29
+ beam_4_max_contexts_4_max_states_8 5.17 best for test
30
+
31
+ 2022-06-22 14:35:00,353 INFO [decode.py:675] Done!
log/fast_beam_search/log-decode-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8-2022-06-22-15-58-14 ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 2022-06-22 15:58:14,422 INFO [decode.py:536] Decoding started
2
+ 2022-06-22 15:58:14,422 INFO [decode.py:542] Device: cuda:0
3
+ 2022-06-22 15:58:14,567 INFO [lexicon.py:176] Loading pre-compiled data/lang_char/Linv.pt
4
+ 2022-06-22 15:58:14,590 INFO [decode.py:552] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 50, 'reset_interval': 100, 'valid_interval': 2000, 'feature_dim': 80, 'subsampling_factor': 4, 'model_warm_step': 1000, 'env_info': {'k2-version': '1.15.1', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f8d2dba06c000ffee36aab5b66f24e7c9809f116', 'k2-git-date': 'Thu Apr 21 12:20:34 2022', 'lhotse-version': '1.4.0.dev+git.94e9ed9.clean', 'torch-version': '1.11.0', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'pruned-rnnt5-recipe-for-tal-csasr', 'icefall-git-sha1': 'c1c893b-dirty', 'icefall-git-date': 'Thu Jun 16 19:19:00 2022', 'icefall-path': '/ceph-meixu/luomingshuang/icefall', 'k2-path': '/ceph-ms/luomingshuang/k2_latest/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-meixu/luomingshuang/anaconda3/envs/k2-python/lib/python3.8/site-packages/lhotse-1.4.0.dev0+git.94e9ed9.clean-py3.8.egg/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-3-0602204318-5799c545db-hhjfr', 'IP address': '10.177.24.137'}, 'epoch': 30, 'iter': 0, 'avg': 24, 'use_averaged_model': False, 'exp_dir': PosixPath('pruned_transducer_stateless5/exp'), 'lang_dir': 'data/lang_char', 'decoding_method': 'fast_beam_search', 'beam_size': 4, 'beam': 4, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'num_encoder_layers': 24, 'dim_feedforward': 1536, 'nhead': 8, 'encoder_dim': 384, 'decoder_dim': 512, 'joiner_dim': 512, 'manifest_dir': PosixPath('data/fbank_new'), 'max_duration': 1500, 'bucketing_sampler': True, 'num_buckets': 300, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'input_strategy': 'PrecomputedFeatures', 'res_dir': PosixPath('pruned_transducer_stateless5/exp/fast_beam_search'), 'suffix': 'epoch-30-avg-24-beam-4-max-contexts-4-max-states-8', 'blank_id': 0, 'vocab_size': 7341}
5
+ 2022-06-22 15:58:14,590 INFO [decode.py:554] About to create model
6
+ 2022-06-22 15:58:15,205 INFO [decode.py:583] averaging ['pruned_transducer_stateless5/exp/epoch-7.pt', 'pruned_transducer_stateless5/exp/epoch-8.pt', 'pruned_transducer_stateless5/exp/epoch-9.pt', 'pruned_transducer_stateless5/exp/epoch-10.pt', 'pruned_transducer_stateless5/exp/epoch-11.pt', 'pruned_transducer_stateless5/exp/epoch-12.pt', 'pruned_transducer_stateless5/exp/epoch-13.pt', 'pruned_transducer_stateless5/exp/epoch-14.pt', 'pruned_transducer_stateless5/exp/epoch-15.pt', 'pruned_transducer_stateless5/exp/epoch-16.pt', 'pruned_transducer_stateless5/exp/epoch-17.pt', 'pruned_transducer_stateless5/exp/epoch-18.pt', 'pruned_transducer_stateless5/exp/epoch-19.pt', 'pruned_transducer_stateless5/exp/epoch-20.pt', 'pruned_transducer_stateless5/exp/epoch-21.pt', 'pruned_transducer_stateless5/exp/epoch-22.pt', 'pruned_transducer_stateless5/exp/epoch-23.pt', 'pruned_transducer_stateless5/exp/epoch-24.pt', 'pruned_transducer_stateless5/exp/epoch-25.pt', 'pruned_transducer_stateless5/exp/epoch-26.pt', 'pruned_transducer_stateless5/exp/epoch-27.pt', 'pruned_transducer_stateless5/exp/epoch-28.pt', 'pruned_transducer_stateless5/exp/epoch-29.pt', 'pruned_transducer_stateless5/exp/epoch-30.pt']
7
+ 2022-06-22 15:58:59,801 INFO [decode.py:643] Number of model parameters: 102139163
8
+ 2022-06-22 15:58:59,801 INFO [asr_datamodule.py:425] About to get dev cuts
9
+ 2022-06-22 15:58:59,803 INFO [asr_datamodule.py:360] About to create dev dataset
10
+ 2022-06-22 15:59:00,137 INFO [asr_datamodule.py:381] About to create dev dataloader
11
+ 2022-06-22 15:59:00,137 INFO [asr_datamodule.py:432] About to get test cuts
12
+ 2022-06-22 15:59:00,735 INFO [asr_datamodule.py:407] About to create test dataloader
13
+ 2022-06-22 15:59:04,439 INFO [decode.py:447] batch 0/?, cuts processed until now is 146
14
+ 2022-06-22 15:59:46,745 INFO [decode.py:464] The transcripts are stored in pruned_transducer_stateless5/exp/fast_beam_search/recogs-dev-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8.txt
15
+ 2022-06-22 15:59:46,886 INFO [utils.py:408] [dev-beam_4_max_contexts_4_max_states_8] %WER 7.32% [8340 / 113916, 1430 ins, 1733 del, 5177 sub ]
16
+ 2022-06-22 15:59:47,274 INFO [decode.py:477] Wrote detailed error stats to pruned_transducer_stateless5/exp/fast_beam_search/errs-dev-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8.txt
17
+ 2022-06-22 15:59:47,275 INFO [decode.py:494]
18
+ For dev, WER of different settings are:
19
+ beam_4_max_contexts_4_max_states_8 7.32 best for dev
20
+
21
+ 2022-06-22 15:59:51,160 INFO [decode.py:447] batch 0/?, cuts processed until now is 152
22
+ 2022-06-22 16:00:42,113 INFO [decode.py:447] batch 20/?, cuts processed until now is 4452
23
+ 2022-06-22 16:01:27,292 INFO [decode.py:447] batch 40/?, cuts processed until now is 9633
24
+ 2022-06-22 16:02:04,697 INFO [decode.py:464] The transcripts are stored in pruned_transducer_stateless5/exp/fast_beam_search/recogs-test-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8.txt
25
+ 2022-06-22 16:02:05,126 INFO [utils.py:408] [test-beam_4_max_contexts_4_max_states_8] %WER 7.42% [24848 / 335012, 4075 ins, 5385 del, 15388 sub ]
26
+ 2022-06-22 16:02:06,215 INFO [decode.py:477] Wrote detailed error stats to pruned_transducer_stateless5/exp/fast_beam_search/errs-test-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8.txt
27
+ 2022-06-22 16:02:06,216 INFO [decode.py:494]
28
+ For test, WER of different settings are:
29
+ beam_4_max_contexts_4_max_states_8 7.42 best for test
30
+
31
+ 2022-06-22 16:02:06,216 INFO [decode.py:680] Done!
log/fast_beam_search/log-decode-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8-use-averaged-model-2022-06-22-18-49-05 ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 2022-06-22 18:49:05,844 INFO [decode.py:536] Decoding started
2
+ 2022-06-22 18:49:05,844 INFO [decode.py:542] Device: cuda:0
3
+ 2022-06-22 18:49:05,953 INFO [lexicon.py:176] Loading pre-compiled data/lang_char/Linv.pt
4
+ 2022-06-22 18:49:05,973 INFO [decode.py:552] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 50, 'reset_interval': 100, 'valid_interval': 2000, 'feature_dim': 80, 'subsampling_factor': 4, 'model_warm_step': 1000, 'env_info': {'k2-version': '1.15.1', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f8d2dba06c000ffee36aab5b66f24e7c9809f116', 'k2-git-date': 'Thu Apr 21 12:20:34 2022', 'lhotse-version': '1.4.0.dev+git.94e9ed9.clean', 'torch-version': '1.11.0', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'pruned-rnnt5-recipe-for-tal-csasr', 'icefall-git-sha1': 'c1c893b-dirty', 'icefall-git-date': 'Thu Jun 16 19:19:00 2022', 'icefall-path': '/ceph-meixu/luomingshuang/icefall', 'k2-path': '/ceph-ms/luomingshuang/k2_latest/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-meixu/luomingshuang/anaconda3/envs/k2-python/lib/python3.8/site-packages/lhotse-1.4.0.dev0+git.94e9ed9.clean-py3.8.egg/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-3-0602204318-5799c545db-hhjfr', 'IP address': '10.177.24.137'}, 'epoch': 30, 'iter': 0, 'avg': 24, 'use_averaged_model': True, 'exp_dir': PosixPath('pruned_transducer_stateless5/exp'), 'lang_dir': 'data/lang_char', 'decoding_method': 'fast_beam_search', 'beam_size': 4, 'beam': 4, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'num_encoder_layers': 24, 'dim_feedforward': 1536, 'nhead': 8, 'encoder_dim': 384, 'decoder_dim': 512, 'joiner_dim': 512, 'manifest_dir': PosixPath('data/fbank_new'), 'max_duration': 1500, 'bucketing_sampler': True, 'num_buckets': 300, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'input_strategy': 'PrecomputedFeatures', 'res_dir': PosixPath('pruned_transducer_stateless5/exp/fast_beam_search'), 'suffix': 'epoch-30-avg-24-beam-4-max-contexts-4-max-states-8-use-averaged-model', 'blank_id': 0, 'vocab_size': 7341}
5
+ 2022-06-22 18:49:05,973 INFO [decode.py:554] About to create model
6
+ 2022-06-22 18:49:06,531 INFO [decode.py:621] Calculating the averaged model over epoch range from 6 (excluded) to 30
7
+ 2022-06-22 18:49:36,534 INFO [decode.py:643] Number of model parameters: 102139163
8
+ 2022-06-22 18:49:36,534 INFO [asr_datamodule.py:425] About to get dev cuts
9
+ 2022-06-22 18:49:36,537 INFO [asr_datamodule.py:360] About to create dev dataset
10
+ 2022-06-22 18:49:36,860 INFO [asr_datamodule.py:381] About to create dev dataloader
11
+ 2022-06-22 18:49:36,860 INFO [asr_datamodule.py:432] About to get test cuts
12
+ 2022-06-22 18:49:37,561 INFO [asr_datamodule.py:407] About to create test dataloader
13
+ 2022-06-22 18:49:41,484 INFO [decode.py:447] batch 0/?, cuts processed until now is 146
14
+ 2022-06-22 18:51:06,045 INFO [decode.py:464] The transcripts are stored in pruned_transducer_stateless5/exp/fast_beam_search/recogs-dev-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8-use-averaged-model.txt
15
+ 2022-06-22 18:51:06,188 INFO [utils.py:408] [dev-beam_4_max_contexts_4_max_states_8] %WER 7.18% [8177 / 113916, 1428 ins, 1702 del, 5047 sub ]
16
+ 2022-06-22 18:51:06,547 INFO [decode.py:477] Wrote detailed error stats to pruned_transducer_stateless5/exp/fast_beam_search/errs-dev-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8-use-averaged-model.txt
17
+ 2022-06-22 18:51:06,548 INFO [decode.py:494]
18
+ For dev, WER of different settings are:
19
+ beam_4_max_contexts_4_max_states_8 7.18 best for dev
20
+
21
+ 2022-06-22 18:51:14,106 INFO [decode.py:447] batch 0/?, cuts processed until now is 152
22
+ 2022-06-22 18:53:14,817 INFO [decode.py:447] batch 20/?, cuts processed until now is 4452
23
+ 2022-06-22 18:53:59,760 INFO [decode.py:447] batch 40/?, cuts processed until now is 9633
24
+ 2022-06-22 18:54:37,231 INFO [decode.py:464] The transcripts are stored in pruned_transducer_stateless5/exp/fast_beam_search/recogs-test-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8-use-averaged-model.txt
25
+ 2022-06-22 18:54:37,627 INFO [utils.py:408] [test-beam_4_max_contexts_4_max_states_8] %WER 7.26% [24329 / 335012, 4106 ins, 5220 del, 15003 sub ]
26
+ 2022-06-22 18:54:38,631 INFO [decode.py:477] Wrote detailed error stats to pruned_transducer_stateless5/exp/fast_beam_search/errs-test-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8-use-averaged-model.txt
27
+ 2022-06-22 18:54:38,631 INFO [decode.py:494]
28
+ For test, WER of different settings are:
29
+ beam_4_max_contexts_4_max_states_8 7.26 best for test
30
+
31
+ 2022-06-22 18:54:38,631 INFO [decode.py:680] Done!
log/fast_beam_search/log-decode-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8-2022-06-22-14-36-05 ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 2022-06-22 14:36:05,889 INFO [decode.py:531] Decoding started
2
+ 2022-06-22 14:36:05,890 INFO [decode.py:537] Device: cuda:0
3
+ 2022-06-22 14:36:06,070 INFO [lexicon.py:176] Loading pre-compiled data/lang_char/Linv.pt
4
+ 2022-06-22 14:36:06,096 INFO [decode.py:547] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 50, 'reset_interval': 100, 'valid_interval': 2000, 'feature_dim': 80, 'subsampling_factor': 4, 'model_warm_step': 1000, 'env_info': {'k2-version': '1.15.1', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f8d2dba06c000ffee36aab5b66f24e7c9809f116', 'k2-git-date': 'Thu Apr 21 12:20:34 2022', 'lhotse-version': '1.4.0.dev+git.94e9ed9.clean', 'torch-version': '1.11.0', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'pruned-rnnt5-recipe-for-tal-csasr', 'icefall-git-sha1': 'c1c893b-dirty', 'icefall-git-date': 'Thu Jun 16 19:19:00 2022', 'icefall-path': '/ceph-meixu/luomingshuang/icefall', 'k2-path': '/ceph-ms/luomingshuang/k2_latest/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-meixu/luomingshuang/anaconda3/envs/k2-python/lib/python3.8/site-packages/lhotse-1.4.0.dev0+git.94e9ed9.clean-py3.8.egg/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-6-0603111709-76b8f59588-flzgf', 'IP address': '10.177.28.73'}, 'epoch': 30, 'iter': 348000, 'avg': 30, 'use_averaged_model': False, 'exp_dir': PosixPath('pruned_transducer_stateless5/exp'), 'lang_dir': 'data/lang_char', 'decoding_method': 'fast_beam_search', 'beam_size': 4, 'beam': 4, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'num_encoder_layers': 24, 'dim_feedforward': 1536, 'nhead': 8, 'encoder_dim': 384, 'decoder_dim': 512, 'joiner_dim': 512, 'manifest_dir': PosixPath('data/fbank_new'), 'max_duration': 1500, 'bucketing_sampler': True, 'num_buckets': 300, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'input_strategy': 'PrecomputedFeatures', 'res_dir': PosixPath('pruned_transducer_stateless5/exp/fast_beam_search'), 'suffix': 'iter-348000-avg-30-beam-4-max-contexts-4-max-states-8', 'blank_id': 0, 'vocab_size': 7341}
5
+ 2022-06-22 14:36:06,097 INFO [decode.py:549] About to create model
6
+ 2022-06-22 14:36:06,903 INFO [decode.py:567] averaging ['pruned_transducer_stateless5/exp/checkpoint-348000.pt', 'pruned_transducer_stateless5/exp/checkpoint-344000.pt', 'pruned_transducer_stateless5/exp/checkpoint-340000.pt', 'pruned_transducer_stateless5/exp/checkpoint-336000.pt', 'pruned_transducer_stateless5/exp/checkpoint-332000.pt', 'pruned_transducer_stateless5/exp/checkpoint-328000.pt', 'pruned_transducer_stateless5/exp/checkpoint-324000.pt', 'pruned_transducer_stateless5/exp/checkpoint-320000.pt', 'pruned_transducer_stateless5/exp/checkpoint-316000.pt', 'pruned_transducer_stateless5/exp/checkpoint-312000.pt', 'pruned_transducer_stateless5/exp/checkpoint-308000.pt', 'pruned_transducer_stateless5/exp/checkpoint-304000.pt', 'pruned_transducer_stateless5/exp/checkpoint-300000.pt', 'pruned_transducer_stateless5/exp/checkpoint-296000.pt', 'pruned_transducer_stateless5/exp/checkpoint-292000.pt', 'pruned_transducer_stateless5/exp/checkpoint-288000.pt', 'pruned_transducer_stateless5/exp/checkpoint-284000.pt', 'pruned_transducer_stateless5/exp/checkpoint-280000.pt', 'pruned_transducer_stateless5/exp/checkpoint-276000.pt', 'pruned_transducer_stateless5/exp/checkpoint-272000.pt', 'pruned_transducer_stateless5/exp/checkpoint-268000.pt', 'pruned_transducer_stateless5/exp/checkpoint-264000.pt', 'pruned_transducer_stateless5/exp/checkpoint-260000.pt', 'pruned_transducer_stateless5/exp/checkpoint-256000.pt', 'pruned_transducer_stateless5/exp/checkpoint-252000.pt', 'pruned_transducer_stateless5/exp/checkpoint-248000.pt', 'pruned_transducer_stateless5/exp/checkpoint-244000.pt', 'pruned_transducer_stateless5/exp/checkpoint-240000.pt', 'pruned_transducer_stateless5/exp/checkpoint-236000.pt', 'pruned_transducer_stateless5/exp/checkpoint-232000.pt']
7
+ 2022-06-22 14:38:27,948 INFO [decode.py:638] Number of model parameters: 102139163
8
+ 2022-06-22 14:38:27,948 INFO [asr_datamodule.py:425] About to get dev cuts
9
+ 2022-06-22 14:38:27,954 INFO [asr_datamodule.py:360] About to create dev dataset
10
+ 2022-06-22 14:38:28,495 INFO [asr_datamodule.py:381] About to create dev dataloader
11
+ 2022-06-22 14:38:28,495 INFO [asr_datamodule.py:432] About to get test cuts
12
+ 2022-06-22 14:38:29,584 INFO [asr_datamodule.py:407] About to create test dataloader
13
+ 2022-06-22 14:38:34,821 INFO [decode.py:442] batch 0/?, cuts processed until now is 146
14
+ 2022-06-22 14:39:22,811 INFO [decode.py:459] The transcripts are stored in pruned_transducer_stateless5/exp/fast_beam_search/recogs-dev-beam_4_max_contexts_4_max_states_8-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8.txt
15
+ 2022-06-22 14:39:23,161 INFO [utils.py:408] [dev-beam_4_max_contexts_4_max_states_8] %WER 5.06% [11156 / 220284, 2620 ins, 3303 del, 5233 sub ]
16
+ 2022-06-22 14:39:24,319 INFO [decode.py:472] Wrote detailed error stats to pruned_transducer_stateless5/exp/fast_beam_search/errs-dev-beam_4_max_contexts_4_max_states_8-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8.txt
17
+ 2022-06-22 14:39:24,320 INFO [decode.py:489]
18
+ For dev, WER of different settings are:
19
+ beam_4_max_contexts_4_max_states_8 5.06 best for dev
20
+
21
+ 2022-06-22 14:39:29,115 INFO [decode.py:442] batch 0/?, cuts processed until now is 152
22
+ 2022-06-22 14:40:24,845 INFO [decode.py:442] batch 20/?, cuts processed until now is 4452
23
+ 2022-06-22 14:41:14,628 INFO [decode.py:442] batch 40/?, cuts processed until now is 9633
24
+ 2022-06-22 14:41:56,932 INFO [decode.py:459] The transcripts are stored in pruned_transducer_stateless5/exp/fast_beam_search/recogs-test-beam_4_max_contexts_4_max_states_8-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8.txt
25
+ 2022-06-22 14:41:57,998 INFO [utils.py:408] [test-beam_4_max_contexts_4_max_states_8] %WER 5.17% [33556 / 648871, 7730 ins, 10083 del, 15743 sub ]
26
+ 2022-06-22 14:42:01,293 INFO [decode.py:472] Wrote detailed error stats to pruned_transducer_stateless5/exp/fast_beam_search/errs-test-beam_4_max_contexts_4_max_states_8-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8.txt
27
+ 2022-06-22 14:42:01,294 INFO [decode.py:489]
28
+ For test, WER of different settings are:
29
+ beam_4_max_contexts_4_max_states_8 5.17 best for test
30
+
31
+ 2022-06-22 14:42:01,294 INFO [decode.py:675] Done!
log/fast_beam_search/log-decode-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8-2022-06-22-15-26-26 ADDED
@@ -0,0 +1,13 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 2022-06-22 15:26:26,446 INFO [decode.py:533] Decoding started
2
+ 2022-06-22 15:26:26,447 INFO [decode.py:539] Device: cuda:0
3
+ 2022-06-22 15:26:26,582 INFO [lexicon.py:176] Loading pre-compiled data/lang_char/Linv.pt
4
+ 2022-06-22 15:26:26,616 INFO [decode.py:549] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 50, 'reset_interval': 100, 'valid_interval': 2000, 'feature_dim': 80, 'subsampling_factor': 4, 'model_warm_step': 1000, 'env_info': {'k2-version': '1.15.1', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f8d2dba06c000ffee36aab5b66f24e7c9809f116', 'k2-git-date': 'Thu Apr 21 12:20:34 2022', 'lhotse-version': '1.4.0.dev+git.94e9ed9.clean', 'torch-version': '1.11.0', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'pruned-rnnt5-recipe-for-tal-csasr', 'icefall-git-sha1': 'c1c893b-dirty', 'icefall-git-date': 'Thu Jun 16 19:19:00 2022', 'icefall-path': '/ceph-meixu/luomingshuang/icefall', 'k2-path': '/ceph-ms/luomingshuang/k2_latest/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-meixu/luomingshuang/anaconda3/envs/k2-python/lib/python3.8/site-packages/lhotse-1.4.0.dev0+git.94e9ed9.clean-py3.8.egg/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-3-0602204318-5799c545db-hhjfr', 'IP address': '10.177.24.137'}, 'epoch': 30, 'iter': 348000, 'avg': 30, 'use_averaged_model': False, 'exp_dir': PosixPath('pruned_transducer_stateless5/exp'), 'lang_dir': 'data/lang_char', 'decoding_method': 'fast_beam_search', 'beam_size': 4, 'beam': 4, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'num_encoder_layers': 24, 'dim_feedforward': 1536, 'nhead': 8, 'encoder_dim': 384, 'decoder_dim': 512, 'joiner_dim': 512, 'manifest_dir': PosixPath('data/fbank_new'), 'max_duration': 1500, 'bucketing_sampler': True, 'num_buckets': 300, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'input_strategy': 'PrecomputedFeatures', 'res_dir': PosixPath('pruned_transducer_stateless5/exp/fast_beam_search'), 'suffix': 'iter-348000-avg-30-beam-4-max-contexts-4-max-states-8', 'blank_id': 0, 'vocab_size': 7341}
5
+ 2022-06-22 15:26:26,616 INFO [decode.py:551] About to create model
6
+ 2022-06-22 15:26:27,191 INFO [decode.py:569] averaging ['pruned_transducer_stateless5/exp/checkpoint-348000.pt', 'pruned_transducer_stateless5/exp/checkpoint-344000.pt', 'pruned_transducer_stateless5/exp/checkpoint-340000.pt', 'pruned_transducer_stateless5/exp/checkpoint-336000.pt', 'pruned_transducer_stateless5/exp/checkpoint-332000.pt', 'pruned_transducer_stateless5/exp/checkpoint-328000.pt', 'pruned_transducer_stateless5/exp/checkpoint-324000.pt', 'pruned_transducer_stateless5/exp/checkpoint-320000.pt', 'pruned_transducer_stateless5/exp/checkpoint-316000.pt', 'pruned_transducer_stateless5/exp/checkpoint-312000.pt', 'pruned_transducer_stateless5/exp/checkpoint-308000.pt', 'pruned_transducer_stateless5/exp/checkpoint-304000.pt', 'pruned_transducer_stateless5/exp/checkpoint-300000.pt', 'pruned_transducer_stateless5/exp/checkpoint-296000.pt', 'pruned_transducer_stateless5/exp/checkpoint-292000.pt', 'pruned_transducer_stateless5/exp/checkpoint-288000.pt', 'pruned_transducer_stateless5/exp/checkpoint-284000.pt', 'pruned_transducer_stateless5/exp/checkpoint-280000.pt', 'pruned_transducer_stateless5/exp/checkpoint-276000.pt', 'pruned_transducer_stateless5/exp/checkpoint-272000.pt', 'pruned_transducer_stateless5/exp/checkpoint-268000.pt', 'pruned_transducer_stateless5/exp/checkpoint-264000.pt', 'pruned_transducer_stateless5/exp/checkpoint-260000.pt', 'pruned_transducer_stateless5/exp/checkpoint-256000.pt', 'pruned_transducer_stateless5/exp/checkpoint-252000.pt', 'pruned_transducer_stateless5/exp/checkpoint-248000.pt', 'pruned_transducer_stateless5/exp/checkpoint-244000.pt', 'pruned_transducer_stateless5/exp/checkpoint-240000.pt', 'pruned_transducer_stateless5/exp/checkpoint-236000.pt', 'pruned_transducer_stateless5/exp/checkpoint-232000.pt']
7
+ 2022-06-22 15:31:08,513 INFO [decode.py:640] Number of model parameters: 102139163
8
+ 2022-06-22 15:31:08,513 INFO [asr_datamodule.py:425] About to get dev cuts
9
+ 2022-06-22 15:31:17,893 INFO [asr_datamodule.py:360] About to create dev dataset
10
+ 2022-06-22 15:31:18,194 INFO [asr_datamodule.py:381] About to create dev dataloader
11
+ 2022-06-22 15:31:18,194 INFO [asr_datamodule.py:432] About to get test cuts
12
+ 2022-06-22 15:31:18,831 INFO [asr_datamodule.py:407] About to create test dataloader
13
+ 2022-06-22 15:31:23,082 INFO [decode.py:444] batch 0/?, cuts processed until now is 146
log/fast_beam_search/log-decode-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8-2022-06-22-15-34-36 ADDED
@@ -0,0 +1,13 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 2022-06-22 15:34:36,307 INFO [decode.py:533] Decoding started
2
+ 2022-06-22 15:34:36,307 INFO [decode.py:539] Device: cuda:0
3
+ 2022-06-22 15:34:36,454 INFO [lexicon.py:176] Loading pre-compiled data/lang_char/Linv.pt
4
+ 2022-06-22 15:34:36,477 INFO [decode.py:549] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 50, 'reset_interval': 100, 'valid_interval': 2000, 'feature_dim': 80, 'subsampling_factor': 4, 'model_warm_step': 1000, 'env_info': {'k2-version': '1.15.1', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f8d2dba06c000ffee36aab5b66f24e7c9809f116', 'k2-git-date': 'Thu Apr 21 12:20:34 2022', 'lhotse-version': '1.4.0.dev+git.94e9ed9.clean', 'torch-version': '1.11.0', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'pruned-rnnt5-recipe-for-tal-csasr', 'icefall-git-sha1': 'c1c893b-dirty', 'icefall-git-date': 'Thu Jun 16 19:19:00 2022', 'icefall-path': '/ceph-meixu/luomingshuang/icefall', 'k2-path': '/ceph-ms/luomingshuang/k2_latest/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-meixu/luomingshuang/anaconda3/envs/k2-python/lib/python3.8/site-packages/lhotse-1.4.0.dev0+git.94e9ed9.clean-py3.8.egg/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-3-0602204318-5799c545db-hhjfr', 'IP address': '10.177.24.137'}, 'epoch': 30, 'iter': 348000, 'avg': 30, 'use_averaged_model': False, 'exp_dir': PosixPath('pruned_transducer_stateless5/exp'), 'lang_dir': 'data/lang_char', 'decoding_method': 'fast_beam_search', 'beam_size': 4, 'beam': 4, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'num_encoder_layers': 24, 'dim_feedforward': 1536, 'nhead': 8, 'encoder_dim': 384, 'decoder_dim': 512, 'joiner_dim': 512, 'manifest_dir': PosixPath('data/fbank_new'), 'max_duration': 1500, 'bucketing_sampler': True, 'num_buckets': 300, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'input_strategy': 'PrecomputedFeatures', 'res_dir': PosixPath('pruned_transducer_stateless5/exp/fast_beam_search'), 'suffix': 'iter-348000-avg-30-beam-4-max-contexts-4-max-states-8', 'blank_id': 0, 'vocab_size': 7341}
5
+ 2022-06-22 15:34:36,477 INFO [decode.py:551] About to create model
6
+ 2022-06-22 15:34:37,070 INFO [decode.py:569] averaging ['pruned_transducer_stateless5/exp/checkpoint-348000.pt', 'pruned_transducer_stateless5/exp/checkpoint-344000.pt', 'pruned_transducer_stateless5/exp/checkpoint-340000.pt', 'pruned_transducer_stateless5/exp/checkpoint-336000.pt', 'pruned_transducer_stateless5/exp/checkpoint-332000.pt', 'pruned_transducer_stateless5/exp/checkpoint-328000.pt', 'pruned_transducer_stateless5/exp/checkpoint-324000.pt', 'pruned_transducer_stateless5/exp/checkpoint-320000.pt', 'pruned_transducer_stateless5/exp/checkpoint-316000.pt', 'pruned_transducer_stateless5/exp/checkpoint-312000.pt', 'pruned_transducer_stateless5/exp/checkpoint-308000.pt', 'pruned_transducer_stateless5/exp/checkpoint-304000.pt', 'pruned_transducer_stateless5/exp/checkpoint-300000.pt', 'pruned_transducer_stateless5/exp/checkpoint-296000.pt', 'pruned_transducer_stateless5/exp/checkpoint-292000.pt', 'pruned_transducer_stateless5/exp/checkpoint-288000.pt', 'pruned_transducer_stateless5/exp/checkpoint-284000.pt', 'pruned_transducer_stateless5/exp/checkpoint-280000.pt', 'pruned_transducer_stateless5/exp/checkpoint-276000.pt', 'pruned_transducer_stateless5/exp/checkpoint-272000.pt', 'pruned_transducer_stateless5/exp/checkpoint-268000.pt', 'pruned_transducer_stateless5/exp/checkpoint-264000.pt', 'pruned_transducer_stateless5/exp/checkpoint-260000.pt', 'pruned_transducer_stateless5/exp/checkpoint-256000.pt', 'pruned_transducer_stateless5/exp/checkpoint-252000.pt', 'pruned_transducer_stateless5/exp/checkpoint-248000.pt', 'pruned_transducer_stateless5/exp/checkpoint-244000.pt', 'pruned_transducer_stateless5/exp/checkpoint-240000.pt', 'pruned_transducer_stateless5/exp/checkpoint-236000.pt', 'pruned_transducer_stateless5/exp/checkpoint-232000.pt']
7
+ 2022-06-22 15:35:30,116 INFO [decode.py:640] Number of model parameters: 102139163
8
+ 2022-06-22 15:35:30,116 INFO [asr_datamodule.py:425] About to get dev cuts
9
+ 2022-06-22 15:35:30,119 INFO [asr_datamodule.py:360] About to create dev dataset
10
+ 2022-06-22 15:35:30,418 INFO [asr_datamodule.py:381] About to create dev dataloader
11
+ 2022-06-22 15:35:30,418 INFO [asr_datamodule.py:432] About to get test cuts
12
+ 2022-06-22 15:35:31,023 INFO [asr_datamodule.py:407] About to create test dataloader
13
+ 2022-06-22 15:35:34,690 INFO [decode.py:444] batch 0/?, cuts processed until now is 146
log/fast_beam_search/log-decode-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8-2022-06-22-15-40-50 ADDED
@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 2022-06-22 15:40:50,400 INFO [decode.py:532] Decoding started
2
+ 2022-06-22 15:40:50,401 INFO [decode.py:538] Device: cuda:0
3
+ 2022-06-22 15:40:50,518 INFO [lexicon.py:176] Loading pre-compiled data/lang_char/Linv.pt
4
+ 2022-06-22 15:40:50,536 INFO [decode.py:548] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 50, 'reset_interval': 100, 'valid_interval': 2000, 'feature_dim': 80, 'subsampling_factor': 4, 'model_warm_step': 1000, 'env_info': {'k2-version': '1.15.1', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f8d2dba06c000ffee36aab5b66f24e7c9809f116', 'k2-git-date': 'Thu Apr 21 12:20:34 2022', 'lhotse-version': '1.4.0.dev+git.94e9ed9.clean', 'torch-version': '1.11.0', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'pruned-rnnt5-recipe-for-tal-csasr', 'icefall-git-sha1': 'c1c893b-dirty', 'icefall-git-date': 'Thu Jun 16 19:19:00 2022', 'icefall-path': '/ceph-meixu/luomingshuang/icefall', 'k2-path': '/ceph-ms/luomingshuang/k2_latest/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-meixu/luomingshuang/anaconda3/envs/k2-python/lib/python3.8/site-packages/lhotse-1.4.0.dev0+git.94e9ed9.clean-py3.8.egg/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-3-0602204318-5799c545db-hhjfr', 'IP address': '10.177.24.137'}, 'epoch': 30, 'iter': 348000, 'avg': 30, 'use_averaged_model': False, 'exp_dir': PosixPath('pruned_transducer_stateless5/exp'), 'lang_dir': 'data/lang_char', 'decoding_method': 'fast_beam_search', 'beam_size': 4, 'beam': 4, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'num_encoder_layers': 24, 'dim_feedforward': 1536, 'nhead': 8, 'encoder_dim': 384, 'decoder_dim': 512, 'joiner_dim': 512, 'manifest_dir': PosixPath('data/fbank_new'), 'max_duration': 1500, 'bucketing_sampler': True, 'num_buckets': 300, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'input_strategy': 'PrecomputedFeatures', 'res_dir': PosixPath('pruned_transducer_stateless5/exp/fast_beam_search'), 'suffix': 'iter-348000-avg-30-beam-4-max-contexts-4-max-states-8', 'blank_id': 0, 'vocab_size': 7341}
5
+ 2022-06-22 15:40:50,536 INFO [decode.py:550] About to create model
6
+ 2022-06-22 15:40:51,112 INFO [decode.py:568] averaging ['pruned_transducer_stateless5/exp/checkpoint-348000.pt', 'pruned_transducer_stateless5/exp/checkpoint-344000.pt', 'pruned_transducer_stateless5/exp/checkpoint-340000.pt', 'pruned_transducer_stateless5/exp/checkpoint-336000.pt', 'pruned_transducer_stateless5/exp/checkpoint-332000.pt', 'pruned_transducer_stateless5/exp/checkpoint-328000.pt', 'pruned_transducer_stateless5/exp/checkpoint-324000.pt', 'pruned_transducer_stateless5/exp/checkpoint-320000.pt', 'pruned_transducer_stateless5/exp/checkpoint-316000.pt', 'pruned_transducer_stateless5/exp/checkpoint-312000.pt', 'pruned_transducer_stateless5/exp/checkpoint-308000.pt', 'pruned_transducer_stateless5/exp/checkpoint-304000.pt', 'pruned_transducer_stateless5/exp/checkpoint-300000.pt', 'pruned_transducer_stateless5/exp/checkpoint-296000.pt', 'pruned_transducer_stateless5/exp/checkpoint-292000.pt', 'pruned_transducer_stateless5/exp/checkpoint-288000.pt', 'pruned_transducer_stateless5/exp/checkpoint-284000.pt', 'pruned_transducer_stateless5/exp/checkpoint-280000.pt', 'pruned_transducer_stateless5/exp/checkpoint-276000.pt', 'pruned_transducer_stateless5/exp/checkpoint-272000.pt', 'pruned_transducer_stateless5/exp/checkpoint-268000.pt', 'pruned_transducer_stateless5/exp/checkpoint-264000.pt', 'pruned_transducer_stateless5/exp/checkpoint-260000.pt', 'pruned_transducer_stateless5/exp/checkpoint-256000.pt', 'pruned_transducer_stateless5/exp/checkpoint-252000.pt', 'pruned_transducer_stateless5/exp/checkpoint-248000.pt', 'pruned_transducer_stateless5/exp/checkpoint-244000.pt', 'pruned_transducer_stateless5/exp/checkpoint-240000.pt', 'pruned_transducer_stateless5/exp/checkpoint-236000.pt', 'pruned_transducer_stateless5/exp/checkpoint-232000.pt']
7
+ 2022-06-22 15:41:42,973 INFO [decode.py:639] Number of model parameters: 102139163
8
+ 2022-06-22 15:41:42,974 INFO [asr_datamodule.py:425] About to get dev cuts
9
+ 2022-06-22 15:41:42,976 INFO [asr_datamodule.py:360] About to create dev dataset
10
+ 2022-06-22 15:41:43,279 INFO [asr_datamodule.py:381] About to create dev dataloader
11
+ 2022-06-22 15:41:43,279 INFO [asr_datamodule.py:432] About to get test cuts
12
+ 2022-06-22 15:41:43,877 INFO [asr_datamodule.py:407] About to create test dataloader
13
+ 2022-06-22 15:41:47,551 INFO [decode.py:443] batch 0/?, cuts processed until now is 146
14
+ 2022-06-22 15:42:29,755 INFO [decode.py:460] The transcripts are stored in pruned_transducer_stateless5/exp/fast_beam_search/recogs-dev-beam_4_max_contexts_4_max_states_8-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8.txt
15
+ 2022-06-22 15:42:29,935 INFO [utils.py:408] [dev-beam_4_max_contexts_4_max_states_8] %WER 99.16% [112962 / 113916, 106140 ins, 455 del, 6367 sub ]
16
+ 2022-06-22 15:42:30,672 INFO [decode.py:473] Wrote detailed error stats to pruned_transducer_stateless5/exp/fast_beam_search/errs-dev-beam_4_max_contexts_4_max_states_8-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8.txt
17
+ 2022-06-22 15:42:30,673 INFO [decode.py:490]
18
+ For dev, WER of different settings are:
19
+ beam_4_max_contexts_4_max_states_8 99.16 best for dev
20
+
21
+ 2022-06-22 15:42:35,078 INFO [decode.py:443] batch 0/?, cuts processed until now is 152
22
+ 2022-06-22 15:43:25,043 INFO [decode.py:443] batch 20/?, cuts processed until now is 4452
23
+ 2022-06-22 15:44:10,013 INFO [decode.py:443] batch 40/?, cuts processed until now is 9633
log/fast_beam_search/log-decode-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8-2022-06-22-15-44-21 ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 2022-06-22 15:44:21,727 INFO [decode.py:536] Decoding started
2
+ 2022-06-22 15:44:21,727 INFO [decode.py:542] Device: cuda:0
3
+ 2022-06-22 15:44:21,837 INFO [lexicon.py:176] Loading pre-compiled data/lang_char/Linv.pt
4
+ 2022-06-22 15:44:21,857 INFO [decode.py:552] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 50, 'reset_interval': 100, 'valid_interval': 2000, 'feature_dim': 80, 'subsampling_factor': 4, 'model_warm_step': 1000, 'env_info': {'k2-version': '1.15.1', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f8d2dba06c000ffee36aab5b66f24e7c9809f116', 'k2-git-date': 'Thu Apr 21 12:20:34 2022', 'lhotse-version': '1.4.0.dev+git.94e9ed9.clean', 'torch-version': '1.11.0', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'pruned-rnnt5-recipe-for-tal-csasr', 'icefall-git-sha1': 'c1c893b-dirty', 'icefall-git-date': 'Thu Jun 16 19:19:00 2022', 'icefall-path': '/ceph-meixu/luomingshuang/icefall', 'k2-path': '/ceph-ms/luomingshuang/k2_latest/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-meixu/luomingshuang/anaconda3/envs/k2-python/lib/python3.8/site-packages/lhotse-1.4.0.dev0+git.94e9ed9.clean-py3.8.egg/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-3-0602204318-5799c545db-hhjfr', 'IP address': '10.177.24.137'}, 'epoch': 30, 'iter': 348000, 'avg': 30, 'use_averaged_model': False, 'exp_dir': PosixPath('pruned_transducer_stateless5/exp'), 'lang_dir': 'data/lang_char', 'decoding_method': 'fast_beam_search', 'beam_size': 4, 'beam': 4, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'num_encoder_layers': 24, 'dim_feedforward': 1536, 'nhead': 8, 'encoder_dim': 384, 'decoder_dim': 512, 'joiner_dim': 512, 'manifest_dir': PosixPath('data/fbank_new'), 'max_duration': 1500, 'bucketing_sampler': True, 'num_buckets': 300, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'input_strategy': 'PrecomputedFeatures', 'res_dir': PosixPath('pruned_transducer_stateless5/exp/fast_beam_search'), 'suffix': 'iter-348000-avg-30-beam-4-max-contexts-4-max-states-8', 'blank_id': 0, 'vocab_size': 7341}
5
+ 2022-06-22 15:44:21,857 INFO [decode.py:554] About to create model
6
+ 2022-06-22 15:44:22,467 INFO [decode.py:572] averaging ['pruned_transducer_stateless5/exp/checkpoint-348000.pt', 'pruned_transducer_stateless5/exp/checkpoint-344000.pt', 'pruned_transducer_stateless5/exp/checkpoint-340000.pt', 'pruned_transducer_stateless5/exp/checkpoint-336000.pt', 'pruned_transducer_stateless5/exp/checkpoint-332000.pt', 'pruned_transducer_stateless5/exp/checkpoint-328000.pt', 'pruned_transducer_stateless5/exp/checkpoint-324000.pt', 'pruned_transducer_stateless5/exp/checkpoint-320000.pt', 'pruned_transducer_stateless5/exp/checkpoint-316000.pt', 'pruned_transducer_stateless5/exp/checkpoint-312000.pt', 'pruned_transducer_stateless5/exp/checkpoint-308000.pt', 'pruned_transducer_stateless5/exp/checkpoint-304000.pt', 'pruned_transducer_stateless5/exp/checkpoint-300000.pt', 'pruned_transducer_stateless5/exp/checkpoint-296000.pt', 'pruned_transducer_stateless5/exp/checkpoint-292000.pt', 'pruned_transducer_stateless5/exp/checkpoint-288000.pt', 'pruned_transducer_stateless5/exp/checkpoint-284000.pt', 'pruned_transducer_stateless5/exp/checkpoint-280000.pt', 'pruned_transducer_stateless5/exp/checkpoint-276000.pt', 'pruned_transducer_stateless5/exp/checkpoint-272000.pt', 'pruned_transducer_stateless5/exp/checkpoint-268000.pt', 'pruned_transducer_stateless5/exp/checkpoint-264000.pt', 'pruned_transducer_stateless5/exp/checkpoint-260000.pt', 'pruned_transducer_stateless5/exp/checkpoint-256000.pt', 'pruned_transducer_stateless5/exp/checkpoint-252000.pt', 'pruned_transducer_stateless5/exp/checkpoint-248000.pt', 'pruned_transducer_stateless5/exp/checkpoint-244000.pt', 'pruned_transducer_stateless5/exp/checkpoint-240000.pt', 'pruned_transducer_stateless5/exp/checkpoint-236000.pt', 'pruned_transducer_stateless5/exp/checkpoint-232000.pt']
7
+ 2022-06-22 15:45:14,417 INFO [decode.py:643] Number of model parameters: 102139163
8
+ 2022-06-22 15:45:14,417 INFO [asr_datamodule.py:425] About to get dev cuts
9
+ 2022-06-22 15:45:14,420 INFO [asr_datamodule.py:360] About to create dev dataset
10
+ 2022-06-22 15:45:14,725 INFO [asr_datamodule.py:381] About to create dev dataloader
11
+ 2022-06-22 15:45:14,725 INFO [asr_datamodule.py:432] About to get test cuts
12
+ 2022-06-22 15:45:15,324 INFO [asr_datamodule.py:407] About to create test dataloader
13
+ 2022-06-22 15:45:18,895 INFO [decode.py:447] batch 0/?, cuts processed until now is 146
14
+ 2022-06-22 15:46:00,664 INFO [decode.py:464] The transcripts are stored in pruned_transducer_stateless5/exp/fast_beam_search/recogs-dev-beam_4_max_contexts_4_max_states_8-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8.txt
15
+ 2022-06-22 15:46:00,798 INFO [utils.py:408] [dev-beam_4_max_contexts_4_max_states_8] %WER 7.25% [8255 / 113916, 1438 ins, 1775 del, 5042 sub ]
16
+ 2022-06-22 15:46:01,144 INFO [decode.py:477] Wrote detailed error stats to pruned_transducer_stateless5/exp/fast_beam_search/errs-dev-beam_4_max_contexts_4_max_states_8-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8.txt
17
+ 2022-06-22 15:46:01,144 INFO [decode.py:494]
18
+ For dev, WER of different settings are:
19
+ beam_4_max_contexts_4_max_states_8 7.25 best for dev
20
+
21
+ 2022-06-22 15:46:04,992 INFO [decode.py:447] batch 0/?, cuts processed until now is 152
22
+ 2022-06-22 15:46:54,671 INFO [decode.py:447] batch 20/?, cuts processed until now is 4452
23
+ 2022-06-22 15:47:39,304 INFO [decode.py:447] batch 40/?, cuts processed until now is 9633
24
+ 2022-06-22 15:48:16,568 INFO [decode.py:464] The transcripts are stored in pruned_transducer_stateless5/exp/fast_beam_search/recogs-test-beam_4_max_contexts_4_max_states_8-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8.txt
25
+ 2022-06-22 15:48:16,984 INFO [utils.py:408] [test-beam_4_max_contexts_4_max_states_8] %WER 7.39% [24766 / 335012, 4196 ins, 5460 del, 15110 sub ]
26
+ 2022-06-22 15:48:17,997 INFO [decode.py:477] Wrote detailed error stats to pruned_transducer_stateless5/exp/fast_beam_search/errs-test-beam_4_max_contexts_4_max_states_8-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8.txt
27
+ 2022-06-22 15:48:17,998 INFO [decode.py:494]
28
+ For test, WER of different settings are:
29
+ beam_4_max_contexts_4_max_states_8 7.39 best for test
30
+
31
+ 2022-06-22 15:48:17,998 INFO [decode.py:680] Done!
log/fast_beam_search/recogs-dev-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8-use-averaged-model.txt ADDED
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log/fast_beam_search/recogs-dev-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8.txt ADDED
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log/fast_beam_search/recogs-dev-beam_4_max_contexts_4_max_states_8-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8.txt ADDED
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log/fast_beam_search/recogs-test-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8-use-averaged-model.txt ADDED
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log/fast_beam_search/recogs-test-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8.txt ADDED
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log/fast_beam_search/recogs-test-beam_4_max_contexts_4_max_states_8-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8.txt ADDED
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log/fast_beam_search/wer-summary-dev-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8-use-averaged-model.txt ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ settings WER
2
+ beam_4_max_contexts_4_max_states_8 7.18
log/fast_beam_search/wer-summary-dev-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8.txt ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ settings WER
2
+ beam_4_max_contexts_4_max_states_8 7.32
log/fast_beam_search/wer-summary-dev-beam_4_max_contexts_4_max_states_8-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8.txt ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ settings WER
2
+ beam_4_max_contexts_4_max_states_8 7.25
log/fast_beam_search/wer-summary-test-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8-use-averaged-model.txt ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ settings WER
2
+ beam_4_max_contexts_4_max_states_8 7.26
log/fast_beam_search/wer-summary-test-beam_4_max_contexts_4_max_states_8-epoch-30-avg-24-beam-4-max-contexts-4-max-states-8.txt ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ settings WER
2
+ beam_4_max_contexts_4_max_states_8 7.42
log/fast_beam_search/wer-summary-test-beam_4_max_contexts_4_max_states_8-iter-348000-avg-30-beam-4-max-contexts-4-max-states-8.txt ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ settings WER
2
+ beam_4_max_contexts_4_max_states_8 7.39
log/greedy_search/errs-dev-greedy_search-epoch-30-avg-24-context-2-max-sym-per-frame-1-use-averaged-model.txt ADDED
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log/greedy_search/errs-dev-greedy_search-epoch-30-avg-24-context-2-max-sym-per-frame-1.txt ADDED
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log/greedy_search/errs-dev-greedy_search-iter-348000-avg-30-context-2-max-sym-per-frame-1.txt ADDED
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log/greedy_search/errs-test-greedy_search-epoch-30-avg-24-context-2-max-sym-per-frame-1-use-averaged-model.txt ADDED
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log/greedy_search/errs-test-greedy_search-epoch-30-avg-24-context-2-max-sym-per-frame-1.txt ADDED
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log/greedy_search/errs-test-greedy_search-iter-348000-avg-30-context-2-max-sym-per-frame-1.txt ADDED
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log/greedy_search/log-decode-epoch-30-avg-24-context-2-max-sym-per-frame-1-2022-06-23-14-56-02 ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 2022-06-23 14:56:02,155 INFO [decode.py:536] Decoding started
2
+ 2022-06-23 14:56:02,155 INFO [decode.py:542] Device: cuda:0
3
+ 2022-06-23 14:56:02,262 INFO [lexicon.py:176] Loading pre-compiled data/lang_char/Linv.pt
4
+ 2022-06-23 14:56:02,280 INFO [decode.py:552] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 50, 'reset_interval': 100, 'valid_interval': 2000, 'feature_dim': 80, 'subsampling_factor': 4, 'model_warm_step': 1000, 'env_info': {'k2-version': '1.15.1', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f8d2dba06c000ffee36aab5b66f24e7c9809f116', 'k2-git-date': 'Thu Apr 21 12:20:34 2022', 'lhotse-version': '1.4.0.dev+git.94e9ed9.clean', 'torch-version': '1.11.0', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'pruned-rnnt5-recipe-for-tal-csasr', 'icefall-git-sha1': 'c1c893b-dirty', 'icefall-git-date': 'Thu Jun 16 19:19:00 2022', 'icefall-path': '/ceph-meixu/luomingshuang/icefall', 'k2-path': '/ceph-ms/luomingshuang/k2_latest/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-meixu/luomingshuang/anaconda3/envs/k2-python/lib/python3.8/site-packages/lhotse-1.4.0.dev0+git.94e9ed9.clean-py3.8.egg/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-1-0307195509-54c966b95f-rtpfq', 'IP address': '10.177.22.9'}, 'epoch': 30, 'iter': 0, 'avg': 24, 'use_averaged_model': False, 'exp_dir': PosixPath('pruned_transducer_stateless5/exp'), 'lang_dir': 'data/lang_char', 'decoding_method': 'greedy_search', 'beam_size': 4, 'beam': 4, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'num_encoder_layers': 24, 'dim_feedforward': 1536, 'nhead': 8, 'encoder_dim': 384, 'decoder_dim': 512, 'joiner_dim': 512, 'manifest_dir': PosixPath('data/fbank_new'), 'max_duration': 800, 'bucketing_sampler': True, 'num_buckets': 300, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'input_strategy': 'PrecomputedFeatures', 'res_dir': PosixPath('pruned_transducer_stateless5/exp/greedy_search'), 'suffix': 'epoch-30-avg-24-context-2-max-sym-per-frame-1', 'blank_id': 0, 'vocab_size': 7341}
5
+ 2022-06-23 14:56:02,280 INFO [decode.py:554] About to create model
6
+ 2022-06-23 14:56:02,848 INFO [decode.py:583] averaging ['pruned_transducer_stateless5/exp/epoch-7.pt', 'pruned_transducer_stateless5/exp/epoch-8.pt', 'pruned_transducer_stateless5/exp/epoch-9.pt', 'pruned_transducer_stateless5/exp/epoch-10.pt', 'pruned_transducer_stateless5/exp/epoch-11.pt', 'pruned_transducer_stateless5/exp/epoch-12.pt', 'pruned_transducer_stateless5/exp/epoch-13.pt', 'pruned_transducer_stateless5/exp/epoch-14.pt', 'pruned_transducer_stateless5/exp/epoch-15.pt', 'pruned_transducer_stateless5/exp/epoch-16.pt', 'pruned_transducer_stateless5/exp/epoch-17.pt', 'pruned_transducer_stateless5/exp/epoch-18.pt', 'pruned_transducer_stateless5/exp/epoch-19.pt', 'pruned_transducer_stateless5/exp/epoch-20.pt', 'pruned_transducer_stateless5/exp/epoch-21.pt', 'pruned_transducer_stateless5/exp/epoch-22.pt', 'pruned_transducer_stateless5/exp/epoch-23.pt', 'pruned_transducer_stateless5/exp/epoch-24.pt', 'pruned_transducer_stateless5/exp/epoch-25.pt', 'pruned_transducer_stateless5/exp/epoch-26.pt', 'pruned_transducer_stateless5/exp/epoch-27.pt', 'pruned_transducer_stateless5/exp/epoch-28.pt', 'pruned_transducer_stateless5/exp/epoch-29.pt', 'pruned_transducer_stateless5/exp/epoch-30.pt']
7
+ 2022-06-23 14:59:46,996 INFO [decode.py:643] Number of model parameters: 102139163
8
+ 2022-06-23 14:59:46,997 INFO [asr_datamodule.py:425] About to get dev cuts
9
+ 2022-06-23 14:59:47,016 INFO [asr_datamodule.py:360] About to create dev dataset
10
+ 2022-06-23 14:59:47,313 INFO [asr_datamodule.py:381] About to create dev dataloader
11
+ 2022-06-23 14:59:47,314 INFO [asr_datamodule.py:432] About to get test cuts
12
+ 2022-06-23 14:59:47,923 INFO [asr_datamodule.py:407] About to create test dataloader
13
+ 2022-06-23 14:59:50,343 INFO [decode.py:447] batch 0/?, cuts processed until now is 78
14
+ 2022-06-23 15:00:18,745 INFO [decode.py:464] The transcripts are stored in pruned_transducer_stateless5/exp/greedy_search/recogs-dev-greedy_search-epoch-30-avg-24-context-2-max-sym-per-frame-1.txt
15
+ 2022-06-23 15:00:18,876 INFO [utils.py:410] [dev-greedy_search] %WER 7.49% [8536 / 113916, 1426 ins, 1987 del, 5123 sub ]
16
+ 2022-06-23 15:00:19,220 INFO [decode.py:477] Wrote detailed error stats to pruned_transducer_stateless5/exp/greedy_search/errs-dev-greedy_search-epoch-30-avg-24-context-2-max-sym-per-frame-1.txt
17
+ 2022-06-23 15:00:19,221 INFO [decode.py:494]
18
+ For dev, WER of different settings are:
19
+ greedy_search 7.49 best for dev
20
+
21
+ 2022-06-23 15:00:21,538 INFO [decode.py:447] batch 0/?, cuts processed until now is 82
22
+ 2022-06-23 15:01:02,499 INFO [decode.py:447] batch 50/?, cuts processed until now is 6627
23
+ 2022-06-23 15:01:42,587 INFO [decode.py:447] batch 100/?, cuts processed until now is 14092
24
+ 2022-06-23 15:01:47,856 INFO [decode.py:464] The transcripts are stored in pruned_transducer_stateless5/exp/greedy_search/recogs-test-greedy_search-epoch-30-avg-24-context-2-max-sym-per-frame-1.txt
25
+ 2022-06-23 15:01:48,253 INFO [utils.py:410] [test-greedy_search] %WER 7.58% [25384 / 335012, 4025 ins, 5992 del, 15367 sub ]
26
+ 2022-06-23 15:01:49,238 INFO [decode.py:477] Wrote detailed error stats to pruned_transducer_stateless5/exp/greedy_search/errs-test-greedy_search-epoch-30-avg-24-context-2-max-sym-per-frame-1.txt
27
+ 2022-06-23 15:01:49,239 INFO [decode.py:494]
28
+ For test, WER of different settings are:
29
+ greedy_search 7.58 best for test
30
+
31
+ 2022-06-23 15:01:49,239 INFO [decode.py:680] Done!
log/greedy_search/log-decode-epoch-30-avg-24-context-2-max-sym-per-frame-1-use-averaged-model-2022-06-23-15-03-06 ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 2022-06-23 15:03:06,191 INFO [decode.py:536] Decoding started
2
+ 2022-06-23 15:03:06,191 INFO [decode.py:542] Device: cuda:0
3
+ 2022-06-23 15:03:06,298 INFO [lexicon.py:176] Loading pre-compiled data/lang_char/Linv.pt
4
+ 2022-06-23 15:03:06,315 INFO [decode.py:552] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 50, 'reset_interval': 100, 'valid_interval': 2000, 'feature_dim': 80, 'subsampling_factor': 4, 'model_warm_step': 1000, 'env_info': {'k2-version': '1.15.1', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f8d2dba06c000ffee36aab5b66f24e7c9809f116', 'k2-git-date': 'Thu Apr 21 12:20:34 2022', 'lhotse-version': '1.4.0.dev+git.94e9ed9.clean', 'torch-version': '1.11.0', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'pruned-rnnt5-recipe-for-tal-csasr', 'icefall-git-sha1': 'c1c893b-dirty', 'icefall-git-date': 'Thu Jun 16 19:19:00 2022', 'icefall-path': '/ceph-meixu/luomingshuang/icefall', 'k2-path': '/ceph-ms/luomingshuang/k2_latest/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-meixu/luomingshuang/anaconda3/envs/k2-python/lib/python3.8/site-packages/lhotse-1.4.0.dev0+git.94e9ed9.clean-py3.8.egg/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-1-0307195509-54c966b95f-rtpfq', 'IP address': '10.177.22.9'}, 'epoch': 30, 'iter': 0, 'avg': 24, 'use_averaged_model': True, 'exp_dir': PosixPath('pruned_transducer_stateless5/exp'), 'lang_dir': 'data/lang_char', 'decoding_method': 'greedy_search', 'beam_size': 4, 'beam': 4, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'num_encoder_layers': 24, 'dim_feedforward': 1536, 'nhead': 8, 'encoder_dim': 384, 'decoder_dim': 512, 'joiner_dim': 512, 'manifest_dir': PosixPath('data/fbank_new'), 'max_duration': 800, 'bucketing_sampler': True, 'num_buckets': 300, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'input_strategy': 'PrecomputedFeatures', 'res_dir': PosixPath('pruned_transducer_stateless5/exp/greedy_search'), 'suffix': 'epoch-30-avg-24-context-2-max-sym-per-frame-1-use-averaged-model', 'blank_id': 0, 'vocab_size': 7341}
5
+ 2022-06-23 15:03:06,315 INFO [decode.py:554] About to create model
6
+ 2022-06-23 15:03:06,919 INFO [decode.py:621] Calculating the averaged model over epoch range from 6 (excluded) to 30
7
+ 2022-06-23 15:03:13,988 INFO [decode.py:643] Number of model parameters: 102139163
8
+ 2022-06-23 15:03:13,988 INFO [asr_datamodule.py:425] About to get dev cuts
9
+ 2022-06-23 15:03:13,991 INFO [asr_datamodule.py:360] About to create dev dataset
10
+ 2022-06-23 15:03:14,289 INFO [asr_datamodule.py:381] About to create dev dataloader
11
+ 2022-06-23 15:03:14,289 INFO [asr_datamodule.py:432] About to get test cuts
12
+ 2022-06-23 15:03:14,884 INFO [asr_datamodule.py:407] About to create test dataloader
13
+ 2022-06-23 15:03:16,776 INFO [decode.py:447] batch 0/?, cuts processed until now is 78
14
+ 2022-06-23 15:03:45,168 INFO [decode.py:464] The transcripts are stored in pruned_transducer_stateless5/exp/greedy_search/recogs-dev-greedy_search-epoch-30-avg-24-context-2-max-sym-per-frame-1-use-averaged-model.txt
15
+ 2022-06-23 15:03:45,297 INFO [utils.py:410] [dev-greedy_search] %WER 7.30% [8318 / 113916, 1384 ins, 1921 del, 5013 sub ]
16
+ 2022-06-23 15:03:45,639 INFO [decode.py:477] Wrote detailed error stats to pruned_transducer_stateless5/exp/greedy_search/errs-dev-greedy_search-epoch-30-avg-24-context-2-max-sym-per-frame-1-use-averaged-model.txt
17
+ 2022-06-23 15:03:45,639 INFO [decode.py:494]
18
+ For dev, WER of different settings are:
19
+ greedy_search 7.3 best for dev
20
+
21
+ 2022-06-23 15:03:47,602 INFO [decode.py:447] batch 0/?, cuts processed until now is 82
22
+ 2022-06-23 15:04:28,459 INFO [decode.py:447] batch 50/?, cuts processed until now is 6627
23
+ 2022-06-23 15:05:08,790 INFO [decode.py:447] batch 100/?, cuts processed until now is 14092
24
+ 2022-06-23 15:05:14,097 INFO [decode.py:464] The transcripts are stored in pruned_transducer_stateless5/exp/greedy_search/recogs-test-greedy_search-epoch-30-avg-24-context-2-max-sym-per-frame-1-use-averaged-model.txt
25
+ 2022-06-23 15:05:14,484 INFO [utils.py:410] [test-greedy_search] %WER 7.39% [24750 / 335012, 4023 ins, 5746 del, 14981 sub ]
26
+ 2022-06-23 15:05:15,485 INFO [decode.py:477] Wrote detailed error stats to pruned_transducer_stateless5/exp/greedy_search/errs-test-greedy_search-epoch-30-avg-24-context-2-max-sym-per-frame-1-use-averaged-model.txt
27
+ 2022-06-23 15:05:15,485 INFO [decode.py:494]
28
+ For test, WER of different settings are:
29
+ greedy_search 7.39 best for test
30
+
31
+ 2022-06-23 15:05:15,486 INFO [decode.py:680] Done!
log/greedy_search/log-decode-iter-348000-avg-30-context-2-max-sym-per-frame-1-2022-06-23-15-06-00 ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 2022-06-23 15:06:00,422 INFO [decode.py:536] Decoding started
2
+ 2022-06-23 15:06:00,422 INFO [decode.py:542] Device: cuda:0
3
+ 2022-06-23 15:06:00,539 INFO [lexicon.py:176] Loading pre-compiled data/lang_char/Linv.pt
4
+ 2022-06-23 15:06:00,560 INFO [decode.py:552] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 50, 'reset_interval': 100, 'valid_interval': 2000, 'feature_dim': 80, 'subsampling_factor': 4, 'model_warm_step': 1000, 'env_info': {'k2-version': '1.15.1', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f8d2dba06c000ffee36aab5b66f24e7c9809f116', 'k2-git-date': 'Thu Apr 21 12:20:34 2022', 'lhotse-version': '1.4.0.dev+git.94e9ed9.clean', 'torch-version': '1.11.0', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'pruned-rnnt5-recipe-for-tal-csasr', 'icefall-git-sha1': 'c1c893b-dirty', 'icefall-git-date': 'Thu Jun 16 19:19:00 2022', 'icefall-path': '/ceph-meixu/luomingshuang/icefall', 'k2-path': '/ceph-ms/luomingshuang/k2_latest/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-meixu/luomingshuang/anaconda3/envs/k2-python/lib/python3.8/site-packages/lhotse-1.4.0.dev0+git.94e9ed9.clean-py3.8.egg/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-1-0307195509-54c966b95f-rtpfq', 'IP address': '10.177.22.9'}, 'epoch': 30, 'iter': 348000, 'avg': 30, 'use_averaged_model': False, 'exp_dir': PosixPath('pruned_transducer_stateless5/exp'), 'lang_dir': 'data/lang_char', 'decoding_method': 'greedy_search', 'beam_size': 4, 'beam': 4, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'num_encoder_layers': 24, 'dim_feedforward': 1536, 'nhead': 8, 'encoder_dim': 384, 'decoder_dim': 512, 'joiner_dim': 512, 'manifest_dir': PosixPath('data/fbank_new'), 'max_duration': 800, 'bucketing_sampler': True, 'num_buckets': 300, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'input_strategy': 'PrecomputedFeatures', 'res_dir': PosixPath('pruned_transducer_stateless5/exp/greedy_search'), 'suffix': 'iter-348000-avg-30-context-2-max-sym-per-frame-1', 'blank_id': 0, 'vocab_size': 7341}
5
+ 2022-06-23 15:06:00,561 INFO [decode.py:554] About to create model
6
+ 2022-06-23 15:06:01,134 INFO [decode.py:572] averaging ['pruned_transducer_stateless5/exp/checkpoint-348000.pt', 'pruned_transducer_stateless5/exp/checkpoint-344000.pt', 'pruned_transducer_stateless5/exp/checkpoint-340000.pt', 'pruned_transducer_stateless5/exp/checkpoint-336000.pt', 'pruned_transducer_stateless5/exp/checkpoint-332000.pt', 'pruned_transducer_stateless5/exp/checkpoint-328000.pt', 'pruned_transducer_stateless5/exp/checkpoint-324000.pt', 'pruned_transducer_stateless5/exp/checkpoint-320000.pt', 'pruned_transducer_stateless5/exp/checkpoint-316000.pt', 'pruned_transducer_stateless5/exp/checkpoint-312000.pt', 'pruned_transducer_stateless5/exp/checkpoint-308000.pt', 'pruned_transducer_stateless5/exp/checkpoint-304000.pt', 'pruned_transducer_stateless5/exp/checkpoint-300000.pt', 'pruned_transducer_stateless5/exp/checkpoint-296000.pt', 'pruned_transducer_stateless5/exp/checkpoint-292000.pt', 'pruned_transducer_stateless5/exp/checkpoint-288000.pt', 'pruned_transducer_stateless5/exp/checkpoint-284000.pt', 'pruned_transducer_stateless5/exp/checkpoint-280000.pt', 'pruned_transducer_stateless5/exp/checkpoint-276000.pt', 'pruned_transducer_stateless5/exp/checkpoint-272000.pt', 'pruned_transducer_stateless5/exp/checkpoint-268000.pt', 'pruned_transducer_stateless5/exp/checkpoint-264000.pt', 'pruned_transducer_stateless5/exp/checkpoint-260000.pt', 'pruned_transducer_stateless5/exp/checkpoint-256000.pt', 'pruned_transducer_stateless5/exp/checkpoint-252000.pt', 'pruned_transducer_stateless5/exp/checkpoint-248000.pt', 'pruned_transducer_stateless5/exp/checkpoint-244000.pt', 'pruned_transducer_stateless5/exp/checkpoint-240000.pt', 'pruned_transducer_stateless5/exp/checkpoint-236000.pt', 'pruned_transducer_stateless5/exp/checkpoint-232000.pt']
7
+ 2022-06-23 15:10:47,130 INFO [decode.py:643] Number of model parameters: 102139163
8
+ 2022-06-23 15:10:47,130 INFO [asr_datamodule.py:425] About to get dev cuts
9
+ 2022-06-23 15:10:47,136 INFO [asr_datamodule.py:360] About to create dev dataset
10
+ 2022-06-23 15:10:47,477 INFO [asr_datamodule.py:381] About to create dev dataloader
11
+ 2022-06-23 15:10:47,477 INFO [asr_datamodule.py:432] About to get test cuts
12
+ 2022-06-23 15:10:48,070 INFO [asr_datamodule.py:407] About to create test dataloader
13
+ 2022-06-23 15:10:49,997 INFO [decode.py:447] batch 0/?, cuts processed until now is 78
14
+ 2022-06-23 15:11:18,396 INFO [decode.py:464] The transcripts are stored in pruned_transducer_stateless5/exp/greedy_search/recogs-dev-greedy_search-iter-348000-avg-30-context-2-max-sym-per-frame-1.txt
15
+ 2022-06-23 15:11:18,527 INFO [utils.py:410] [dev-greedy_search] %WER 7.46% [8500 / 113916, 1429 ins, 2023 del, 5048 sub ]
16
+ 2022-06-23 15:11:18,873 INFO [decode.py:477] Wrote detailed error stats to pruned_transducer_stateless5/exp/greedy_search/errs-dev-greedy_search-iter-348000-avg-30-context-2-max-sym-per-frame-1.txt
17
+ 2022-06-23 15:11:18,873 INFO [decode.py:494]
18
+ For dev, WER of different settings are:
19
+ greedy_search 7.46 best for dev
20
+
21
+ 2022-06-23 15:11:20,850 INFO [decode.py:447] batch 0/?, cuts processed until now is 82
22
+ 2022-06-23 15:12:01,670 INFO [decode.py:447] batch 50/?, cuts processed until now is 6627
23
+ 2022-06-23 15:12:41,886 INFO [decode.py:447] batch 100/?, cuts processed until now is 14092
24
+ 2022-06-23 15:12:47,122 INFO [decode.py:464] The transcripts are stored in pruned_transducer_stateless5/exp/greedy_search/recogs-test-greedy_search-iter-348000-avg-30-context-2-max-sym-per-frame-1.txt
25
+ 2022-06-23 15:12:47,519 INFO [utils.py:410] [test-greedy_search] %WER 7.54% [25247 / 335012, 4175 ins, 5993 del, 15079 sub ]
26
+ 2022-06-23 15:12:48,519 INFO [decode.py:477] Wrote detailed error stats to pruned_transducer_stateless5/exp/greedy_search/errs-test-greedy_search-iter-348000-avg-30-context-2-max-sym-per-frame-1.txt
27
+ 2022-06-23 15:12:48,520 INFO [decode.py:494]
28
+ For test, WER of different settings are:
29
+ greedy_search 7.54 best for test
30
+
31
+ 2022-06-23 15:12:48,520 INFO [decode.py:680] Done!
log/greedy_search/recogs-dev-greedy_search-epoch-30-avg-24-context-2-max-sym-per-frame-1-use-averaged-model.txt ADDED
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log/greedy_search/recogs-dev-greedy_search-epoch-30-avg-24-context-2-max-sym-per-frame-1.txt ADDED
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log/greedy_search/recogs-dev-greedy_search-iter-348000-avg-30-context-2-max-sym-per-frame-1.txt ADDED
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log/greedy_search/recogs-test-greedy_search-epoch-30-avg-24-context-2-max-sym-per-frame-1-use-averaged-model.txt ADDED
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log/greedy_search/recogs-test-greedy_search-epoch-30-avg-24-context-2-max-sym-per-frame-1.txt ADDED
The diff for this file is too large to render. See raw diff
 
log/greedy_search/recogs-test-greedy_search-iter-348000-avg-30-context-2-max-sym-per-frame-1.txt ADDED
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log/greedy_search/wer-summary-dev-greedy_search-epoch-30-avg-24-context-2-max-sym-per-frame-1-use-averaged-model.txt ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ settings WER
2
+ greedy_search 7.3
log/greedy_search/wer-summary-dev-greedy_search-epoch-30-avg-24-context-2-max-sym-per-frame-1.txt ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ settings WER
2
+ greedy_search 7.49