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token_type: unigram |
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character_coverage: 1.0 |
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dnn_neurons: 1024 |
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wav2vec_output_dim: 1024 |
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dropout: 0.15 |
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sample_rate: 16000 |
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wav2vec2_hub: facebook/wav2vec2-large-xlsr-53 |
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output_neurons: 1000 |
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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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enc: !new:speechbrain.nnet.containers.Sequential |
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input_shape: [null, null, !ref <wav2vec_output_dim>] |
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linear1: !name:speechbrain.nnet.linear.Linear |
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n_neurons: !ref <dnn_neurons> |
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bias: True |
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bn1: !name:speechbrain.nnet.normalization.BatchNorm1d |
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activation: !new:torch.nn.LeakyReLU |
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drop: !new:torch.nn.Dropout |
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p: !ref <dropout> |
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linear2: !name:speechbrain.nnet.linear.Linear |
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n_neurons: !ref <dnn_neurons> |
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bias: True |
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bn2: !name:speechbrain.nnet.normalization.BatchNorm1d |
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activation2: !new:torch.nn.LeakyReLU |
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drop2: !new:torch.nn.Dropout |
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p: !ref <dropout> |
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linear3: !name:speechbrain.nnet.linear.Linear |
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n_neurons: !ref <dnn_neurons> |
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bias: True |
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bn3: !name:speechbrain.nnet.normalization.BatchNorm1d |
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activation3: !new:torch.nn.LeakyReLU |
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wav2vec2: !new:speechbrain.lobes.models.huggingface_wav2vec.HuggingFaceWav2Vec2 |
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source: !ref <wav2vec2_hub> |
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output_norm: True |
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freeze: True |
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save_path: wav2vec2_checkpoint |
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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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log_softmax: !new:speechbrain.nnet.activations.Softmax |
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apply_log: True |
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ctc_cost: !name:speechbrain.nnet.losses.ctc_loss |
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blank_index: !ref <blank_index> |
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asr_model: !new:torch.nn.ModuleList |
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- [!ref <enc>, !ref <ctc_lin>] |
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tokenizer: !new:sentencepiece.SentencePieceProcessor |
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encoder: !new:speechbrain.nnet.containers.LengthsCapableSequential |
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wav2vec2: !ref <wav2vec2> |
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enc: !ref <enc> |
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ctc_lin: !ref <ctc_lin> |
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modules: |
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encoder: !ref <encoder> |
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decoding_function: !name:speechbrain.decoders.ctc_greedy_decode |
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blank_id: !ref <blank_index> |
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pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer |
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loadables: |
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wav2vec2: !ref <wav2vec2> |
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asr: !ref <asr_model> |
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tokenizer: !ref <tokenizer> |