mirror of
https://github.com/k2-fsa/icefall.git
synced 2025-09-06 15:44:17 +00:00
101 lines
3.0 KiB
Bash
Executable File
101 lines
3.0 KiB
Bash
Executable File
#!/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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set -eou pipefail
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nj=1
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stage=-1
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stop_stage=100
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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/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-1.1 ]; then
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lhotse download ljspeech $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
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# to $dl_dir/LJSpeech
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mkdir -p data/manifests
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if [ ! -e data/manifests/.ljspeech.done ]; then
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lhotse prepare ljspeech $dl_dir/LJSpeech-1.1 data/manifests
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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: Compute spectrogram for LJSpeech"
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mkdir -p data/spectrogram
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if [ ! -e data/spectrogram/.ljspeech.done ]; then
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./local/compute_spectrogram_ljspeech.py
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touch data/spectrogram/.ljspeech.done
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fi
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if [ ! -e data/spectrogram/.ljspeech-validated.done ]; then
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log "Validating data/fbank for LJSpeech"
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python3 ./local/validate_manifest.py \
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data/spectrogram/ljspeech_cuts_all.jsonl.gz
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touch data/spectrogram/.ljspeech-validated.done
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fi
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fi
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if [ $stage -le 3 ] && [ $stop_stage -ge 3 ]; then
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log "Stage 3: Split the LJSpeech cuts into train, valid and test sets"
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if [ ! -e data/spectrogram/.ljspeech_split.done ]; then
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lhotse subset --last 600 \
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data/spectrogram/ljspeech_cuts_all.jsonl.gz \
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data/spectrogram/ljspeech_cuts_validtest.jsonl.gz
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lhotse subset --first 100 \
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data/spectrogram/ljspeech_cuts_validtest.jsonl.gz \
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data/spectrogram/ljspeech_cuts_valid.jsonl.gz
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lhotse subset --last 500 \
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data/spectrogram/ljspeech_cuts_validtest.jsonl.gz \
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data/spectrogram/ljspeech_cuts_test.jsonl.gz
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rm data/spectrogram/ljspeech_cuts_validtest.jsonl.gz
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n=$(( $(gunzip -c data/spectrogram/ljspeech_cuts_all.jsonl.gz | wc -l) - 600 ))
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lhotse subset --first $n \
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data/spectrogram/ljspeech_cuts_all.jsonl.gz \
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data/spectrogram/ljspeech_cuts_train.jsonl.gz
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touch data/spectrogram/.ljspeech_split.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: Generate token file"
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if [ ! -e data/tokens.txt ]; then
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./local/prepare_token_file.py \
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--manifest-file data/spectrogram/ljspeech_cuts_train.jsonl.gz \
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--tokens data/tokens.txt
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fi
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fi
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