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sample_rate: 16000 |
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time_resolution: 0.01 |
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n_fft: 400 |
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n_mels: 40 |
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activation: !name:torch.nn.LeakyReLU |
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dropout: 0.15 |
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cnn_blocks: 2 |
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cnn_channels: (16, 32) |
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cnn_kernelsize: (3, 3) |
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rnn_layers: 2 |
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rnn_neurons: 32 |
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rnn_bidirectional: True |
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dnn_blocks: 1 |
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dnn_neurons: 16 |
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output_neurons: 1 |
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device: 'cpu' |
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compute_features: !new:speechbrain.lobes.features.Fbank |
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sample_rate: !ref <sample_rate> |
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n_fft: !ref <n_fft> |
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n_mels: !ref <n_mels> |
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hop_length: !ref <time_resolution> * 1000 |
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mean_var_norm: !new:speechbrain.processing.features.InputNormalization |
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norm_type: sentence |
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cnn: !new:speechbrain.nnet.containers.Sequential |
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input_shape: [null, null, !ref <n_mels>] |
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norm1: !name:speechbrain.nnet.normalization.LayerNorm |
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cnn1: !name:speechbrain.lobes.models.CRDNN.CNN_Block |
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channels: 16 |
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kernel_size: (3, 3) |
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cnn2: !name:speechbrain.lobes.models.CRDNN.CNN_Block |
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channels: 32 |
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kernel_size: (3, 3) |
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rnn: !new:speechbrain.nnet.RNN.GRU |
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input_shape: [null, null, 320] |
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hidden_size: !ref <rnn_neurons> |
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num_layers: !ref <rnn_layers> |
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bidirectional: True |
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dnn: !new:speechbrain.nnet.containers.Sequential |
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input_shape: [null, null, !ref <rnn_neurons> * 2] |
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dnn1: !name:speechbrain.lobes.models.CRDNN.DNN_Block |
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neurons: !ref <dnn_neurons> |
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dnn2: !name:speechbrain.lobes.models.CRDNN.DNN_Block |
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neurons: !ref <dnn_neurons> |
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lin: !name:speechbrain.nnet.linear.Linear |
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n_neurons: !ref <output_neurons> |
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bias: False |
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model: !new:torch.nn.ModuleList |
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- [!ref <cnn>, !ref <rnn>, !ref <dnn>] |
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modules: |
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compute_features: !ref <compute_features> |
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model: !ref <model> |
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cnn: !ref <cnn> |
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rnn: !ref <rnn> |
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dnn: !ref <dnn> |
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mean_var_norm: !ref <mean_var_norm> |
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pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer |
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loadables: |
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model: !ref <model> |
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mean_var_norm: !ref <mean_var_norm> |
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