| | |
|---|
| | | spm_train --input=${feats_dir}/data/lang_char/input.txt --vocab_size=${nbpe} --model_type=${bpemode} --model_prefix=${bpemodel} --input_sentence_size=100000000 |
|---|
| | | spm_encode --model=${bpemodel}.model --output_format=piece < ${feats_dir}/data/lang_char/input.txt | tr ' ' '\n' | sort | uniq | awk '{print $0}' >> ${dict} |
|---|
| | | echo "<unk>" >> ${dict} |
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| | | wc -l ${dict} |
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| | | |
|---|
| | | vocab_size=$(cat ${dict} | wc -l) |
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| | | awk -v v=,${vocab_size} '{print $0v}' ${feat_train_dir}/text_shape > ${feat_train_dir}/text_shape.char |
|---|
| | | awk -v v=,${vocab_size} '{print $0v}' ${feat_dev_dir}/text_shape > ${feat_dev_dir}/text_shape.char |
|---|
| | | mkdir -p ${feats_dir}/asr_stats_fbank_zh_char/$train_set |
|---|
| | | mkdir -p ${feats_dir}/asr_stats_fbank_zh_char/$valid_set |
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| | | cp ${feat_train_dir}/speech_shape ${feat_train_dir}/text_shape ${feat_train_dir}/text_shape.char ${feats_dir}/asr_stats_fbank_zh_char/$train_set |
|---|
| | | cp ${feat_dev_dir}/speech_shape ${feat_dev_dir}/text_shape ${feat_dev_dir}/text_shape.char ${feats_dir}/asr_stats_fbank_zh_char/$valid_set |
|---|
| | | fi |
|---|
| | | |
|---|
| | | |
|---|
