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n_mels: 80 |
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pretrained_path: gorinars/sb-ecapa-vggsound-simclr |
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out_n_neurons: 308 |
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compute_features: !new:speechbrain.lobes.features.Fbank |
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n_mels: 80 |
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left_frames: 0 |
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right_frames: 0 |
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deltas: false |
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sample_rate: 16000 |
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n_fft: 400 |
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win_length: 25 |
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hop_length: 10 |
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f_min: 0 |
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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.nnet.containers.LengthsCapableSequential |
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input_shape: [null, 1, null] |
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embedding: !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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groups: [1, 1, 1, 1, 1] |
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attention_channels: 128 |
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lin_neurons: 256 |
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projector: !new:crytorch.models.components.pann.SimSiamProjector |
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input_size: 256 |
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hidden_size: 256 |
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output_size: 256 |
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norm_type: bn |
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classifier: !new:speechbrain.lobes.models.ECAPA_TDNN.Classifier |
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input_size: 256 |
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out_neurons: !ref <out_n_neurons> |
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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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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: !ref <embedding_model.embedding> |
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projector: !ref <embedding_model.projector> |
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paths: |
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embedding: !ref <pretrained_path>/embedding_model.ckpt |
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projector: !ref <pretrained_path>/projector.ckpt |
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