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@ -83,6 +83,8 @@ specaug_conf:
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num_time_mask: 2
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dataset_conf:
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data_names: speech,text
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data_types: sound,text
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shuffle: True
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shuffle_conf:
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shuffle_size: 2048
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@ -93,4 +95,4 @@ dataset_conf:
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num_workers: 8
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log_interval: 50
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normalize: None
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normalize: None
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@ -103,8 +103,6 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
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utils/text2token.py -s 1 -n 1 --space "" ${feats_dir}/data/${train_set}/text | cut -f 2- -d" " | tr " " "\n" \
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| sort | uniq | grep -a -v -e '^\s*$' | awk '{print $0}' >> ${token_list}
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echo "<unk>" >> ${token_list}
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mkdir -p ${feats_dir}/asr_stats_fbank_zh_char/${train_set}
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mkdir -p ${feats_dir}/asr_stats_fbank_zh_char/${valid_set}
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fi
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# LM Training Stage
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@ -82,8 +82,6 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
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utils/text2token.py -s 1 -n 1 --space "" ${feats_dir}/data/${train_set}/text | cut -f 2- -d" " | tr " " "\n" \
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| sort | uniq | grep -a -v -e '^\s*$' | awk '{print $0}' >> ${token_list}
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echo "<unk>" >> ${token_list}
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mkdir -p ${feats_dir}/asr_stats_fbank_zh_char/${train_set}
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mkdir -p ${feats_dir}/asr_stats_fbank_zh_char/${valid_set}
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fi
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# Training Stage
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@ -43,7 +43,6 @@ spk_encoder_conf:
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pooling_type: statistic
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num_nodes_resnet1: 256
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num_nodes_last_layer: 256
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batchnorm_momentum: 0.5
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# decoder related
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decoder: sa_decoder
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