hyperparams.yaml

# ############################################################################
# Model: ResNet for Speaker verification
# ############################################################################

# Feature parameters
n_mels: 80

# Pretrain folder (HuggingFace)
pretrained_path: EvGUT/speechbrain_bcm5

# Output parameters
out_n_neurons: 235

# 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.ResNet.ResNet
    input_size: !ref <n_mels>
    channels: [128, 128, 256, 256]
    strides: [1, 2, 2, 2]
    block_sizes: [3, 4, 6, 3]
    lin_neurons: 512

classifier: !new:speechbrain.lobes.models.ResNet.Classifier
    input_size: 512
    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>
        classifier: !ref <classifier>
    paths:
        embedding_model: !ref <pretrained_path>/embedding_model.ckpt
        classifier: !ref <pretrained_path>/classifier.ckpt