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sample_rate: 16000 |
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n_fft: 400 |
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n_mels: 80 |
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activation: !name:torch.nn.LeakyReLU |
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dropout: 0.15 |
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cnn_blocks: 3 |
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cnn_channels: (128, 200, 256) |
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inter_layer_pooling_size: (2, 2, 2) |
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cnn_kernelsize: (3, 3) |
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time_pooling_size: 4 |
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rnn_class: !name:speechbrain.nnet.RNN.LSTM |
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rnn_layers: 5 |
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rnn_neurons: 1024 |
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rnn_bidirectional: True |
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dnn_blocks: 2 |
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dnn_neurons: 1024 |
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dec_neurons: 1024 |
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joint_dim: 1024 |
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output_neurons: 1000 |
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blank_index: 0 |
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bos_index: 0 |
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eos_index: 0 |
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min_decode_ratio: 0.0 |
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max_decode_ratio: 1.0 |
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beam_size: 4 |
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nbest: 1 |
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state_beam: 2.3 |
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expand_beam: 2.3 |
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transducer_beam_search: True |
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normalizer: !new:speechbrain.processing.features.InputNormalization |
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norm_type: global |
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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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enc: !new:speechbrain.lobes.models.CRDNN.CRDNN |
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input_shape: [null, null, !ref <n_mels>] |
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activation: !ref <activation> |
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dropout: !ref <dropout> |
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cnn_blocks: !ref <cnn_blocks> |
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cnn_channels: !ref <cnn_channels> |
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cnn_kernelsize: !ref <cnn_kernelsize> |
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inter_layer_pooling_size: !ref <inter_layer_pooling_size> |
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time_pooling: True |
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using_2d_pooling: False |
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time_pooling_size: !ref <time_pooling_size> |
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rnn_class: !ref <rnn_class> |
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rnn_layers: !ref <rnn_layers> |
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rnn_neurons: !ref <rnn_neurons> |
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rnn_bidirectional: !ref <rnn_bidirectional> |
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rnn_re_init: True |
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dnn_blocks: !ref <dnn_blocks> |
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dnn_neurons: !ref <dnn_neurons> |
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enc_lin: !new:speechbrain.nnet.linear.Linear |
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input_size: !ref <dnn_neurons> |
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n_neurons: !ref <joint_dim> |
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emb: !new:speechbrain.nnet.embedding.Embedding |
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num_embeddings: !ref <output_neurons> |
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consider_as_one_hot: True |
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blank_id: !ref <blank_index> |
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dec: !new:speechbrain.nnet.RNN.GRU |
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input_shape: [null, null, !ref <output_neurons> - 1] |
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hidden_size: !ref <dec_neurons> |
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num_layers: 1 |
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re_init: True |
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dec_lin: !new:speechbrain.nnet.linear.Linear |
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input_size: !ref <dec_neurons> |
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n_neurons: !ref <joint_dim> |
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bias: False |
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Tjoint: !new:speechbrain.nnet.transducer.transducer_joint.Transducer_joint |
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joint: sum |
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nonlinearity: !ref <activation> |
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transducer_lin: !new:speechbrain.nnet.linear.Linear |
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input_size: !ref <joint_dim> |
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n_neurons: !ref <output_neurons> |
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bias: False |
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log_softmax: !new:speechbrain.nnet.activations.Softmax |
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apply_log: True |
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asr_model: !new:torch.nn.ModuleList |
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- [!ref <enc>, !ref <emb>, !ref <dec>, !ref <transducer_lin>] |
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tokenizer: !new:sentencepiece.SentencePieceProcessor |
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encoder: !new:speechbrain.nnet.containers.LengthsCapableSequential |
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input_shape: [null, null, !ref <n_mels>] |
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compute_features: !ref <compute_features> |
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normalize: !ref <normalizer> |
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model: !ref <enc> |
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decoder: !new:speechbrain.decoders.transducer.TransducerBeamSearcher |
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decode_network_lst: [!ref <emb>, !ref <dec>] |
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tjoint: !ref <Tjoint> |
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classifier_network: [!ref <transducer_lin>] |
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blank_id: !ref <blank_index> |
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beam_size: !ref <beam_size> |
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nbest: !ref <nbest> |
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state_beam: !ref <state_beam> |
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expand_beam: !ref <expand_beam> |
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modules: |
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normalizer: !ref <normalizer> |
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encoder: !ref <encoder> |
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decoder: !ref <decoder> |
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pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer |
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loadables: |
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normalizer: !ref <normalizer> |
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asr: !ref <asr_model> |
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tokenizer: !ref <tokenizer> |
