# ############################################################################ # Model: ECAPA big for Speaker verification # ############################################################################ # Feature parameters n_mels: 80 # Pretrain folder (HuggingFace) pretrained_path: speechbrain/spkrec-ecapa-voxceleb # Output parameters out_n_neurons: 7205 # Model params compute_features: !new:speechbrain.lobes.features.Fbank n_mels: !ref <n_mels> mean_var_norm: !new:speechbrain.processing.features.InputNormalization norm_type: sentence std_norm: False embedding_model: !new:speechbrain.lobes.models.ECAPA_TDNN.ECAPA_TDNN input_size: !ref <n_mels> channels: [1024, 1024, 1024, 1024, 3072] kernel_sizes: [5, 3, 3, 3, 1] dilations: [1, 2, 3, 4, 1] attention_channels: 128 lin_neurons: 192 classifier: !new:speechbrain.lobes.models.ECAPA_TDNN.Classifier input_size: 192 out_neurons: !ref <out_n_neurons> mean_var_norm_emb: !new:speechbrain.processing.features.InputNormalization norm_type: global std_norm: False modules: compute_features: !ref <compute_features> mean_var_norm: !ref <mean_var_norm> embedding_model: !ref <embedding_model> mean_var_norm_emb: !ref <mean_var_norm_emb> classifier: !ref <classifier> label_encoder: !new:speechbrain.dataio.encoder.CategoricalEncoder pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer loadables: embedding_model: !ref <embedding_model> mean_var_norm_emb: !ref <mean_var_norm_emb> classifier: !ref <classifier> label_encoder: !ref <label_encoder> paths: embedding_model: !ref <pretrained_path>/embedding_model.ckpt mean_var_norm_emb: !ref <pretrained_path>/mean_var_norm_emb.ckpt classifier: !ref <pretrained_path>/classifier.ckpt label_encoder: !ref <pretrained_path>/label_encoder.txt