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