Update README.md

README.md

@@ -34,13 +34,13 @@ The model can be used directly (without a language model) as follows:
 import torch
 import torchaudio
 import librosa
-from datasets import load_dataset, load_metric
+from datasets import load_dataset
 import MeCab
 from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
 
 # config
 wakati = MeCab.Tagger("-Owakati")
-chars_to_ignore_regex = '[\\\\,\\\\、\\\\。\\\\．\\\\「\\\\」\\\\…\\\\？\\\\・]'
+chars_to_ignore_regex = '[\\\\\\\\,\\\\\\\\、\\\\\\\\。\\\\\\\\．\\\\\\\\「\\\\\\\\」\\\\\\\\…\\\\\\\\？\\\\\\\\・]'
 
 # load data, processor and model
 test_dataset = load_dataset("common_voice", "ja", split="test[:2%]")
@@ -73,13 +73,13 @@ The model can be evaluated as follows on the Japanese test data of Common Voice.
 import torch
 import librosa
 import torchaudio
-from datasets import load_dataset
+from datasets import load_dataset, load_metric
 import MeCab
 from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
 
 #config
 wakati = MeCab.Tagger("-Owakati")
-chars_to_ignore_regex = '[\\\\,\\\\、\\\\。\\\\．\\\\「\\\\」\\\\…\\\\？\\\\・]'
+chars_to_ignore_regex = '[\\\\\\\\,\\\\\\\\、\\\\\\\\。\\\\\\\\．\\\\\\\\「\\\\\\\\」\\\\\\\\…\\\\\\\\？\\\\\\\\・]'
 
 # load data, processor and model
 test_dataset = load_dataset("common_voice", "ja", split="test")