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egs/LJSpeech/ASR/prepare_4446.sh
Executable file
158
egs/LJSpeech/ASR/prepare_4446.sh
Executable file
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#!/usr/bin/env bash
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# fix segmentation fault reported in https://github.com/k2-fsa/icefall/issues/674
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export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python
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#. ../../../tools/activate_python.sh
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set -eou pipefail
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nj=15
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stage=-1
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stop_stage=100
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# We assume dl_dir (download dir) contains the following
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# directories and files. If not, they will be downloaded
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# by this script automatically.
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#
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# - $dl_dir/LJSpeech
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# You can find BOOKS.TXT, test-clean, train-clean-360, etc, inside it.
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# You can download them from https://www.openslr.org/12
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#
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# - $dl_dir/lm
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# This directory contains the following files downloaded from
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# http://www.openslr.org/resources/11
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#
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# - 3-gram.pruned.1e-7.arpa.gz
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# - 3-gram.pruned.1e-7.arpa
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# - 4-gram.arpa.gz
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# - 4-gram.arpa
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# - LJSpeech-vocab.txt
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# - LJSpeech-lexicon.txt
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# - LJSpeech-lm-norm.txt.gz
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#
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# - $dl_dir/musan
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# This directory contains the following directories downloaded from
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# http://www.openslr.org/17/
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#
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# - music
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# - noise
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# - speech
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dl_dir=/DB/LibriSpeech_tar
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. shared/parse_options.sh || exit 1
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# vocab size for sentence piece models.
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# It will generate data/lang_bpe_xxx,
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# data/lang_bpe_yyy if the array contains xxx, yyy
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vocab_sizes=(
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5000
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2000
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1000
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500
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)
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# All files generated by this script are saved in "data".
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# You can safely remove "data" and rerun this script to regenerate it.
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mkdir -p data
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log() {
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# This function is from espnet
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local fname=${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/LJSpeech,
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# you can create a symlink
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#
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# ln -sfv /path/to/LJSpeech $dl_dir/LJSpeech
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#
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if [ ! -d $dl_dir/LJSpeech/wav ]; then
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echo "download not supported yet";
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fi
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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/
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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 LJSpeech manifest"
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# We assume that you have downloaded the LJSpeech corpus (ver 1.1)
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# You need to prepare LJSpeech according to data_settings/*_list.txt like below
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# $dl_dir/LJSpeech
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# |-- wavs
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# | |-- train
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# | |-- dev
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# | |-- test
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# |-- texts
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# |-- metadata.csv
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# to $dl_dir/LJSpeech
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if [ ! -e $dl_dir/LJSpeech/.LJSpeech.done ]; then
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for dset in "train" "dev" "test"; do
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log "Resampling LJSpeech $dset set"
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file_list=`ls $dl_dir/LJSpeech/wavs/$dset/`
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for wavfile in $file_list; do
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sox -v 0.9 $dl_dir/LJSpeech/wavs/$dset/$wavfile -r 16000 -e signed-integer $dl_dir/LJSpeech/wavs/$dset/tmp_$wavfile
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mv $dl_dir/LJSpeech/wavs/$dset/tmp_$wavfile $dl_dir/LJSpeech/wavs/$dset/$wavfile
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done
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log "Resampling $dset done"
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done
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python local/prepare_LJSpeech_text.py $dl_dir/LJSpeech/metadata.csv
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touch $dl_dir/LJSpeech/.LJSpeech.done
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fi
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mkdir -p data/manifests
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if [ ! -e data/manifests/.LJSpeech.done ]; then
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python local/prepare_LJSpeech.py $dl_dir/LJSpeech
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touch data/manifests/.LJSpeech.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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mkdir -p data/manifests
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if [ ! -e data/manifests/.musan.done ]; then
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lhotse prepare musan $dl_dir/musan data/manifests
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touch data/manifests/.musan.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 3: Compute fbank for LJSpeech"
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mkdir -p data/fbank
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if [ ! -e data/fbank/.LJSpeech.done ]; then
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./local/compute_fbank_LJSpeech.py --data-dir $dl_dir/LJSpeech
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touch data/fbank/.LJSpeech.done
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fi
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if [ ! -e data/fbank/.LJSpeech-validated.done ]; then
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log "Validating data/fbank for LJSpeech"
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parts=`ls $dl_dir/LJSpeech/wavs/`
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for part in ${parts[@]}; do
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python3 ./local/validate_manifest.py \
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data/fbank/LJSpeech_cuts_${part}.jsonl.gz
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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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mkdir -p data/fbank
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if [ ! -e data/fbank/.musan.done ]; then
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./local/compute_fbank_musan.py
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touch data/fbank/.musan.done
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fi
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fi
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