From 23f53a2fcb2cd1a012f1143c3d875664cb38e83d Mon Sep 17 00:00:00 2001 From: speech_asr Date: Tue, 14 Feb 2023 19:29:38 +0800 Subject: [PATCH] update docs --- docs/get_started.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/docs/get_started.md b/docs/get_started.md index dda4d65d6..c62a610ae 100644 --- a/docs/get_started.md +++ b/docs/get_started.md @@ -30,17 +30,17 @@ BAC009S0002W0123 也 成 为 地 方 政 府 的 眼 中 钉 BAC009S0002W0124 自 六 月 底 呼 和 浩 特 市 率 先 宣 布 取 消 限 购 后 ... ``` -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. +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. ## Stage 1: Feature Generation -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: +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: * `feats.scp` ``` ... BAC009S0002W0122_sp0.9 /nfs/funasr_data/aishell-1/dump/fbank/train/ark/feats.16.ark:592751055 ... ``` -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: +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: * `speech_shape` ``` ... @@ -53,7 +53,7 @@ BAC009S0002W0122_sp0.9 665,80 BAC009S0002W0122_sp0.9 15 ... ``` -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. +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. ## Stage 2: Dictionary Preparation 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: