2025-04-16 13:25:40 +09:00

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#!/usr/bin/env bash
# fix segmentation fault reported in https://github.com/k2-fsa/icefall/issues/674
export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python
set -eou pipefail
nj=15
stage=-1
stop_stage=100
# We assume dl_dir (download dir) contains the following
# directories and files. If not, they will be downloaded
# by this script automatically.
#
# - $dl_dir/ReazonSpeech
# You can find FLAC files in this directory.
# You can download them from https://huggingface.co/datasets/reazon-research/reazonspeech
#
# - $dl_dir/ReazonSpeech/dataset.json
# The metadata of the ReazonSpeech dataset.
#
# - $dl_dir/musan
# This directory contains the following directories downloaded from
# http://www.openslr.org/17/
#
# - music
# - noise
# - speech
dl_dir=$PWD/download
. shared/parse_options.sh || exit 1
# All files generated by this script are saved in "data".
# You can safely remove "data" and rerun this script to regenerate it.
mkdir -p data
log() {
# This function is from espnet
local fname=${BASH_SOURCE[1]##*/}
echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
}
log "Running prepare.sh"
log "dl_dir: $dl_dir"
if [ $stage -le 0 ] && [ $stop_stage -ge 0 ]; then
log "Stage 0: Download data"
# If you have pre-downloaded it to /path/to/ReazonSpeech,
# you can create a symlink
#
# ln -sfv /path/to/ReazonSpeech $dl_dir/ReazonSpeech
#
if [ ! -d $dl_dir/ReazonSpeech/downloads ]; then
# Download small-v1 by default.
lhotse download reazonspeech --subset medium $dl_dir
fi
# If you have pre-downloaded it to /path/to/musan,
# you can create a symlink
#
# ln -sfv /path/to/musan $dl_dir/
#
if [ ! -d $dl_dir/musan ]; then
lhotse download musan $dl_dir
fi
fi
if [ $stage -le 1 ] && [ $stop_stage -ge 1 ]; then
log "Stage 1: Prepare ReazonSpeech manifest"
# We assume that you have downloaded the ReazonSpeech corpus
# to $dl_dir/ReazonSpeech
mkdir -p data/manifests
if [ ! -e data/manifests/.reazonspeech.done ]; then
lhotse prepare reazonspeech -j $nj $dl_dir/ReazonSpeech data/manifests
touch data/manifests/.reazonspeech.done
fi
fi
if [ $stage -le 2 ] && [ $stop_stage -ge 2 ]; then
log "Stage 2: Prepare musan manifest"
# We assume that you have downloaded the musan corpus
# to $dl_dir/musan
mkdir -p data/manifests
if [ ! -e data/manifests/.musan_prep.done ]; then
lhotse prepare musan $dl_dir/musan data/manifests
touch data/manifests/.musan_prep.done
fi
fi
if [ $stage -le 3 ] && [ $stop_stage -ge 3 ]; then
log "Stage 3: Compute ReazonSpeech fbank"
if [ ! -e data/manifests/.reazonspeech-validated.done ]; then
python local/compute_fbank_reazonspeech.py --manifest-dir data/manifests
python local/validate_manifest.py --manifest data/manifests/reazonspeech_cuts_train.jsonl.gz
python local/validate_manifest.py --manifest data/manifests/reazonspeech_cuts_dev.jsonl.gz
python local/validate_manifest.py --manifest data/manifests/reazonspeech_cuts_test.jsonl.gz
touch data/manifests/.reazonspeech-validated.done
fi
fi
if [ $stage -le 4 ] && [ $stop_stage -ge 4 ]; then
log "Stage 4: Compute fbank for musan"
mkdir -p data/manifests
if [ ! -e data/manifests/.musan_fbank.done ]; then
./local/compute_fbank_musan.py
touch data/manifests/.musan_fbank.done
fi
fi
if [ $stage -le 5 ] && [ $stop_stage -ge 5 ]; then
log "Stage 5: Prepare ReazonSpeech lang_char"
python local/prepare_lang_char.py data/manifests/reazonspeech_cuts_train.jsonl.gz
fi
if [ $stage -le 6 ] && [ $stop_stage -ge 6 ]; then
log "Stage 6: Show manifest statistics"
python local/display_manifest_statistics.py --manifest-dir data/manifests > data/manifests/manifest_statistics.txt
cat data/manifests/manifest_statistics.txt
fi