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# ############################################################################
# Model: WAV2VEC base for Emotion Recognition
# ############################################################################
# Feature parameters
sample_rate: 16000
wav2vec2_hub: facebook/wav2vec2-base
# Pretrain folder (HuggingFace)
pretrained_path: speechbrain/emotion-recognition-wav2vec2
# parameters
encoder_dim: 768
out_n_neurons: 4
wav2vec2: !new:speechbrain.lobes.models.huggingface_wav2vec.HuggingFaceWav2Vec2
source: !ref <wav2vec2_hub>
output_norm: True
freeze: True
pretrain: False
save_path: wav2vec2_checkpoints
avg_pool: !new:speechbrain.nnet.pooling.StatisticsPooling
return_std: False
output_mlp: !new:speechbrain.nnet.linear.Linear
input_size: !ref <encoder_dim>
n_neurons: !ref <out_n_neurons>
bias: False
model: !new:torch.nn.ModuleList
- [!ref <output_mlp>]
modules:
wav2vec2: !ref <wav2vec2>
output_mlp: !ref <output_mlp>
avg_pool: !ref <avg_pool>
softmax: !new:speechbrain.nnet.activations.Softmax
label_encoder: !new:speechbrain.dataio.encoder.CategoricalEncoder
pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
loadables:
wav2vec2: !ref <wav2vec2>
model: !ref <model>
label_encoder: !ref <label_encoder>
paths:
wav2vec2: !ref <pretrained_path>/wav2vec2.ckpt
model: !ref <pretrained_path>/model.ckpt
label_encoder: !ref <pretrained_path>/label_encoder.txt
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