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# https://yaml.org/type/float.html
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data:
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train_manifest: data/manifest.train
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dev_manifest: data/manifest.dev
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test_manifest: data/manifest.test
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min_input_len: 0.0
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max_input_len: 27.0 # second
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min_output_len: 0.0
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max_output_len: .inf
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min_output_input_ratio: 0.00
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max_output_input_ratio: .inf
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collator:
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batch_size: 64 # one gpu
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mean_std_filepath: data/mean_std.json
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unit_type: char
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vocab_filepath: data/vocab.txt
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augmentation_config: conf/augmentation.json
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random_seed: 0
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spm_model_prefix:
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specgram_type: linear #linear, mfcc, fbank
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feat_dim:
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delta_delta: False
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stride_ms: 10.0
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window_ms: 20.0
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n_fft: None
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max_freq: None
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target_sample_rate: 16000
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use_dB_normalization: True
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target_dB: -20
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dither: 1.0
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keep_transcription_text: False
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sortagrad: True
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shuffle_method: batch_shuffle
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num_workers: 0
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model:
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num_conv_layers: 2
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num_rnn_layers: 5
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rnn_layer_size: 1024
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rnn_direction: forward # [forward, bidirect]
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num_fc_layers: 0
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fc_layers_size_list: -1,
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use_gru: False
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blank_id: 0
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training:
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n_epoch: 50
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lr: 2e-3
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lr_decay: 0.9 # 0.83
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weight_decay: 1e-06
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global_grad_clip: 3.0
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log_interval: 100
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checkpoint:
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kbest_n: 50
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latest_n: 5
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decoding:
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batch_size: 32
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error_rate_type: cer
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decoding_method: ctc_beam_search
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lang_model_path: data/lm/zh_giga.no_cna_cmn.prune01244.klm
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alpha: 2.2 #1.9
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beta: 5.0
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beam_size: 300
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cutoff_prob: 0.99
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cutoff_top_n: 40
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num_proc_bsearch: 10
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