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| | | BAC009S0002W0124 自 六 月 底 呼 和 浩 特 市 率 先 宣 布 取 消 限 购 后 |
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| | | ... |
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| | | ``` |
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| | | These two files both have two columns, while the first column is the wav ids and the second column is the corresponding wav paths/label tokens. |
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| | | These two files both have two columns, while the first column is wav ids and the second column is the corresponding wav paths/label tokens. |
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| | | |
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| | | ## Stage 1: Feature Generation |
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| | | This stage extracts FBank feature from raw wav `wav.scp` and apply speed perturbation as data augmentation according to `speed_perturb`. You can set `nj` to control the number of jobs for feature generation. The output features are saved in `$feats_dir/dump/xxx/ark` and the corresponding `feats.scp` files are saved as `$feats_dir/dump/xxx/feats.scp`. An example of `feats.scp` can be seen as follows: |
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| | | This stage extracts FBank features from `wav.scp` and apply speed perturbation as data augmentation according to `speed_perturb`. Users can set `nj` to control the number of jobs for feature generation. The generated features are saved in `$feats_dir/dump/xxx/ark` and the corresponding `feats.scp` files are saved as `$feats_dir/dump/xxx/feats.scp`. An example of `feats.scp` can be seen as follows: |
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| | | * `feats.scp` |
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| | | ``` |
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| | | ... |
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| | | BAC009S0002W0122_sp0.9 /nfs/funasr_data/aishell-1/dump/fbank/train/ark/feats.16.ark:592751055 |
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| | | ... |
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| | | ``` |
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| | | Note that samples in this file have already been shuffled. This file contains two columns. The first column is the wav-id while the second column is the kaldi-ark feature path. Besides, `speech_shape` and `text_shape` are also generated in this stage, denoting the speech feature shape and text length of each sample. The examples are shown as follows: |
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| | | Note that samples in this file have already been shuffled randomly. This file contains two columns. The first column is wav ids while the second column is kaldi-ark feature paths. Besides, `speech_shape` and `text_shape` are also generated in this stage, denoting the speech feature shape and text length of each sample. The examples are shown as follows: |
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| | | * `speech_shape` |
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| | | ``` |
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| | | ... |
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| | |
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| | | BAC009S0002W0122_sp0.9 15 |
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| | | ... |
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| | | ``` |
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| | | These two files have two columns. The first column is the wav-id and the second column is the corresponding speech feature shape and text length. |
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| | | These two files have two columns. The first column is wav ids and the second column is the corresponding speech feature shape and text length. |
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| | | |
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| | | ## Stage 2: Dictionary Preparation |
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| | | This stage prepares a dictionary, which is used as a mapping between label characters and integer indices during ASR training. The output dictionary file is saved as `$feats_dir/data/$lang_toekn_list/$token_type/tokens.txt`. Here we show an example of `tokens.txt` as follows: |
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