| | |
|---|
| | | - `CUDA_VISIBLE_DEVICES`: `0,1` (Default), visible gpu list |
|---|
| | | - `gpu_num`: `2` (Default), the number of GPUs used for training |
|---|
| | | - `gpu_inference`: `true` (Default), whether to use GPUs for decoding |
|---|
| | | - `njob`: `1` (Default), for CPU decoding, indicating the total number of CPU jobs; for GPU decoding, indicating the number of jobs on each GPU |
|---|
| | | - `njob`: `1` (Default),for CPU decoding, indicating the total number of CPU jobs; for GPU decoding, indicating the number of jobs on each GPU |
|---|
| | | - `raw_data`: the raw path of AISHELL-1 dataset |
|---|
| | | - `feats_dir`: the path for saving processed data |
|---|
| | | - `token_type`: `char` (Default), indicate how to process text |
|---|
| | | - `type`: `sound` (Default), set the input type |
|---|
| | | - `scp`: `wav.scp` (Default), set the input file |
|---|
| | | - `nj`: `64` (Default), the number of jobs for data preparation |
|---|
| | | - `speed_perturb`: `"0.9, 1.0 ,1.1"` (Default), the range of speech perturbed |
|---|
| | | - `exp_dir`: the path for saving experimental results |
|---|
| | |
|---|
| | | |
|---|
| | | ### Stage 2: Dictionary Preparation |
|---|
| | | 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/$token_type/tokens.txt`. An example of `tokens.txt` is as follows: |
|---|
| | | * `tokens.txt` |
|---|
| | | ``` |
|---|
| | | <blank> |
|---|
| | | <s> |
|---|
| | |
|---|
| | | 龟 |
|---|
| | | <unk> |
|---|
| | | ``` |
|---|
| | | * `<blank>`: indicates the blank token for CTC |
|---|
| | | * `<s>`: indicates the start-of-sentence token |
|---|
| | | * `</s>`: indicates the end-of-sentence token |
|---|
| | | * `<unk>`: indicates the out-of-vocabulary token |
|---|
| | | * `<blank>`: indicates the blank token for CTC, must be in the first line |
|---|
| | | * `<s>`: indicates the start-of-sentence token, must be in the second line |
|---|
| | | * `</s>`: indicates the end-of-sentence token, must be in the third line |
|---|
| | | * `<unk>`: indicates the out-of-vocabulary token, must be in the last line |
|---|
| | | |
|---|
| | | ### Stage 3: LM Training |
|---|
| | | |
|---|
| | |
|---|
| | | * Performance |
|---|
| | | |
|---|
| | | We adopt `CER` to verify the performance. The results are in `$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`: |
|---|
| | | * `text.cer` |
|---|
| | | ``` |
|---|
| | | ... |
|---|
| | | BAC009S0764W0213(nwords=11,cor=11,ins=0,del=0,sub=0) corr=100.00%,cer=0.00% |
|---|
