mirror of
https://github.com/k2-fsa/icefall.git
synced 2025-08-26 10:16:14 +00:00
110 lines
3.1 KiB
Bash
Executable File
110 lines
3.1 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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stage=0
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stop_stage=100
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sampling_rate=24000
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nj=32
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perturb_speed=true
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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/LibriTTS,
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# you can create a symlink
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#
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# ln -sfv /path/to/LibriTTS $dl_dir/LibriTTS
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#
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if [ ! -d $dl_dir/LibriTTS ]; then
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lhotse download libritts $dl_dir
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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/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 LibriTTS manifest"
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# We assume that you have downloaded the LibriTTS corpus
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# to $dl_dir/LibriTTS
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mkdir -p data/manifests
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if [ ! -e data/manifests/.libritts.done ]; then
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lhotse prepare libritts --num-jobs 32 $dl_dir/LibriTTS data/manifests
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touch data/manifests/.libritts.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 LibriTTS"
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mkdir -p data/fbank
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if [ ! -e data/fbank/.libritts.done ]; then
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./local/compute_fbank_libritts.py \
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--sampling-rate $sampling_rate \
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--perturb-speed $perturb_speed
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touch data/fbank/.libritts.done
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fi
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# Here we shuffle and combine the train-clean-100, train-clean-360 and
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# train-other-500 together to form the training set.
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if [ ! -f data/fbank/libritts_cuts_train-all-shuf.jsonl.gz ]; then
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cat <(gunzip -c data/fbank/libritts_cuts_train-clean-100.jsonl.gz) \
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<(gunzip -c data/fbank/libritts_cuts_train-clean-360.jsonl.gz) \
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<(gunzip -c data/fbank/libritts_cuts_train-other-500.jsonl.gz) | \
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shuf | gzip -c > data/fbank/libritts_cuts_train-all-shuf.jsonl.gz
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fi
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if [ ! -e data/fbank/.libritts-validated.done ]; then
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log "Validating data/fbank for LibriTTS"
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./local/validate_manifest.py \
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data/fbank/libritts_cuts_train-all-shuf.jsonl.gz
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touch data/fbank/.libritts-validated.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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