mirror of
https://github.com/k2-fsa/icefall.git
synced 2025-09-18 21:44:18 +00:00
141 lines
3.7 KiB
Bash
Executable File
141 lines
3.7 KiB
Bash
Executable File
#!/usr/bin/env bash
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set -eou pipefail
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nj=30
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stage=3
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stop_stage=3
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# We assume dl_dir (download dir) contains the following
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# directories and files. If not, you need to apply aishell2 through
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# their official website.
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#
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# - $dl_dir/aishell2
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#
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#
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# - $dl_dir/musan
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# This directory contains the following directories downloaded from
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# http://www.openslr.org/17/
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#
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# - music
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# - noise
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# - speech
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dl_dir=$PWD/download
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. shared/parse_options.sh || exit 1
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# All files generated by this script are saved in "data".
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# You can safely remove "data" and rerun this script to regenerate it.
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mkdir -p data
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log() {
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# This function is from espnet
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local fname=${BASH_SOURCE[1]##*/}
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echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
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}
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log "dl_dir: $dl_dir"
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if [ $stage -le 0 ] && [ $stop_stage -ge 0 ]; then
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log "stage 0: Download data"
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# If you have pre-downloaded it to /path/to/aishell2,
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# you can create a symlink
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#
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# ln -sfv /path/to/aishell2 $dl_dir/aishell2
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#
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# The directory structure is
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# aishell2/
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# |-- AISHELL-2
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# | |-- iOS
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# |-- data
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# |-- wav
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# |-- trans.txt
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# |-- dev
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# |-- wav
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# |-- trans.txt
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# |-- test
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# |-- wav
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# |-- trans.txt
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# If you have pre-downloaded it to /path/to/musan,
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# you can create a symlink
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#
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# ln -sfv /path/to/musan $dl_dir/musan
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#
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if [ ! -d $dl_dir/musan ]; then
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lhotse download musan $dl_dir
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fi
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fi
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if [ $stage -le 1 ] && [ $stop_stage -ge 1 ]; then
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log "Stage 1: Prepare aishell2 manifest"
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# We assume that you have downloaded and unzip the aishell2 corpus
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# to $dl_dir/aishell2
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if [ ! -f data/manifests/.aishell_manifests.done ]; then
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mkdir -p data/manifests
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lhotse prepare aishell2 $dl_dir/aishell2 data/manifests -j $nj
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touch data/manifests/.aishell2_manifests.done
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fi
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fi
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if [ $stage -le 2 ] && [ $stop_stage -ge 2 ]; then
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log "Stage 2: Prepare musan manifest"
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# We assume that you have downloaded the musan corpus
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# to data/musan
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if [ ! -f data/manifests/.musan_manifests.done ]; then
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log "It may take 6 minutes"
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mkdir -p data/manifests
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lhotse prepare musan $dl_dir/musan data/manifests
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touch data/manifests/.musan_manifests.done
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fi
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fi
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if [ $stage -le 3 ] && [ $stop_stage -ge 3 ]; then
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log "Stage 3: Compute fbank for aishell"
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if [ ! -f data/fbank/.aishell2.done ]; then
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mkdir -p data/fbank
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./local/compute_fbank_aishell2.py
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touch data/fbank/.aishell2.done
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fi
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fi
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if [ $stage -le 4 ] && [ $stop_stage -ge 4 ]; then
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log "Stage 4: Compute fbank for musan"
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if [ ! -f data/fbank/.msuan.done ]; then
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mkdir -p data/fbank
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./local/compute_fbank_musan.py
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touch data/fbank/.msuan.done
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fi
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fi
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if [ $stage -le 5 ] && [ $stop_stage -ge 5 ]; then
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log "Stage 6: Prepare char based lang"
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lang_char_dir=data/lang_char
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mkdir -p $lang_char_dir
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# Prepare text.
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grep "\"text\":" data/manifests/aishell2_supervisions_train.json \
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| sed -e 's/["text:\t ]*//g' | sed 's/,//g' \
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| ./local/text2token.py -t "char" > $lang_char_dir/text
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# Prepare words.txt
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grep "\"text\":" data/manifests/aishell2_supervisions_train.json \
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| sed -e 's/["text:\t]*//g' | sed 's/,//g' \
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| ./local/text2token.py -t "char" > $lang_char_dir/text_words
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cat $lang_char_dir/text_words | sed 's/ /\n/g' | sort -u | sed '/^$/d' \
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| uniq > $lang_char_dir/words_no_ids.txt
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if [ ! -f $lang_char_dir/words.txt ]; then
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./local/prepare_words.py \
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--input-file $lang_char_dir/words_no_ids.txt
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--output-file $lang_char_dir/words.txt
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fi
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if [ ! -f $lang_char_dir/L_disambig.pt ]; then
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./local/prepare_char.py
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fi
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fi |