# ############################################################################ # 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-IEMOCAP # parameters encoder_dim: 768 out_n_neurons: 4 wav2vec2: !new:speechbrain.lobes.models.huggingface_wav2vec.HuggingFaceWav2Vec2 source: !ref 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 n_neurons: !ref bias: False model: !new:torch.nn.ModuleList - [!ref ] modules: wav2vec2: !ref output_mlp: !ref avg_pool: !ref softmax: !new:speechbrain.nnet.activations.Softmax label_encoder: !new:speechbrain.dataio.encoder.CategoricalEncoder pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer loadables: wav2vec2: !ref model: !ref label_encoder: !ref paths: wav2vec2: !ref /wav2vec2.ckpt model: !ref /model.ckpt label_encoder: !ref /label_encoder.txt