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sample_rate: 16000 |
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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: (128, 256) |
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inter_layer_pooling_size: (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: 4 |
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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: 512 |
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emb_size: 128 |
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dec_neurons: 1024 |
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output_neurons: 2000 |
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blank_index: 0 |
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bos_index: 1 |
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eos_index: 2 |
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min_decode_ratio: 0.0 |
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max_decode_ratio: 1.0 |
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valid_beam_size: 60 |
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test_beam_size: 80 |
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eos_threshold: 1.5 |
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using_max_attn_shift: True |
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max_attn_shift: 240 |
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ctc_weight_decode: 0.3 |
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coverage_penalty: 1.8 |
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temperature: 1.25 |
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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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use_rnnp: False |
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emb: !new:speechbrain.nnet.embedding.Embedding |
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num_embeddings: !ref <output_neurons> |
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embedding_dim: !ref <emb_size> |
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dec: !new:speechbrain.nnet.RNN.AttentionalRNNDecoder |
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enc_dim: !ref <dnn_neurons> |
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input_size: !ref <emb_size> |
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rnn_type: gru |
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attn_type: location |
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hidden_size: !ref <dec_neurons> |
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attn_dim: 1024 |
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num_layers: 1 |
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scaling: 1.0 |
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channels: 10 |
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kernel_size: 100 |
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re_init: True |
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dropout: !ref <dropout> |
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ctc_lin: !new:speechbrain.nnet.linear.Linear |
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input_size: !ref <dnn_neurons> |
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n_neurons: !ref <output_neurons> |
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seq_lin: !new:speechbrain.nnet.linear.Linear |
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input_size: !ref <dec_neurons> |
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n_neurons: !ref <output_neurons> |
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log_softmax: !new:speechbrain.nnet.activations.Softmax |
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apply_log: True |
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tokenizer: !new:sentencepiece.SentencePieceProcessor |
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asr_model: !new:torch.nn.ModuleList |
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- [!ref <enc>, !ref <emb>, !ref <dec>, !ref <ctc_lin>, !ref <seq_lin>] |
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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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ctc_scorer: !new:speechbrain.decoders.scorer.CTCScorer |
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eos_index: !ref <eos_index> |
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blank_index: !ref <blank_index> |
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ctc_fc: !ref <ctc_lin> |
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coverage_scorer: !new:speechbrain.decoders.scorer.CoverageScorer |
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vocab_size: !ref <output_neurons> |
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scorer: !new:speechbrain.decoders.scorer.ScorerBuilder |
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full_scorers: [!ref <ctc_scorer>, !ref <coverage_scorer>] |
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weights: |
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ctc: !ref <ctc_weight_decode> |
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coverage: !ref <coverage_penalty> |
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decoder: !new:speechbrain.decoders.S2SRNNBeamSearcher |
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embedding: !ref <emb> |
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decoder: !ref <dec> |
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linear: !ref <seq_lin> |
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bos_index: !ref <bos_index> |
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eos_index: !ref <eos_index> |
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min_decode_ratio: !ref <min_decode_ratio> |
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max_decode_ratio: !ref <max_decode_ratio> |
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beam_size: !ref <test_beam_size> |
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eos_threshold: !ref <eos_threshold> |
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using_max_attn_shift: !ref <using_max_attn_shift> |
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max_attn_shift: !ref <max_attn_shift> |
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temperature: !ref <temperature> |
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scorer: !ref <scorer> |
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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> |
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