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| | | |
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| | | ### Stage 2: Dictionary Preparation |
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| | | This stage processes the dictionary, which is used as a mapping between label characters and integer indices during ASR training. The processed dictionary file is saved as `$feats_dir/data/$lang_toekn_list/$token_type/tokens.txt`. An example of `tokens.txt` is as follows: |
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| | | * `tokens.txt` |
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| | | ``` |
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| | | <blank> |
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| | | <s> |
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| | |
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| | | 龟 |
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| | | <unk> |
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| | | ``` |
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| | | * `<blank>`: indicates the blank token for CTC |
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| | | * `<s>`: indicates the start-of-sentence token |
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| | | * `</s>`: indicates the end-of-sentence token |
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| | | * `<unk>`: indicates the out-of-vocabulary token |
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| | | * `<blank>`: indicates the blank token for CTC, must be in the first line |
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| | | * `<s>`: indicates the start-of-sentence token, must be in the second line |
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| | | * `</s>`: indicates the end-of-sentence token, must be in the third line |
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| | | * `<unk>`: indicates the out-of-vocabulary token, must be in the last line |
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| | | |
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| | | ### Stage 3: LM Training |
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| | | |
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| | | * Performance |
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| | | |
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| | | We adopt `CER` to verify the performance. The results are in `$exp_dir/exp/$model_dir/$decoding_yaml_name/$average_model_name/$dset`, namely `text.cer` and `text.cer.txt`. `text.cer` saves the comparison between the recognized text and the reference text while `text.cer.txt` saves the final `CER` results. The following is an example of `text.cer`: |
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| | | * `text.cer` |
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| | | ``` |
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| | | ... |
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| | | BAC009S0764W0213(nwords=11,cor=11,ins=0,del=0,sub=0) corr=100.00%,cer=0.00% |
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