icefall/egs/tedlium3/ASR/prepare.sh
Mingshuang Luo ad28c8c5eb
Tedlium3 transducer stateless (#233)
* add tedlium3 transducer-stateless
2022-03-18 11:39:06 +08:00

157 lines
4.1 KiB
Bash

#!/usr/bin/env bash
set -eou pipefail
nj=15
stage=0
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/tedlium3
# You can find data, doc, legacy, LM, etc, inside it.
# You can download them from https://www.openslr.org/51
#
# - $dl_dir/musan
# This directory contains the following directories downloaded from
# http://www.openslr.org/17/
#
# - music
# - noise
# - speech
dl_dir=$PWD/download
. shared/parse_options.sh || exit 1
# vocab size for sentence piece models.
# It will generate data/lang_bpe_xxx,
# data/lang_bpe_yyy if the array contains xxx, yyy
vocab_sizes=(
5000
2000
1000
500
)
# 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 "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/tedlium3,
# you can create a symlink
#
# ln -sfv /path/to/tedlium3 $dl_dir/tedlium3
#
if [ ! -d $dl_dir/tedlium3 ]; then
lhotse download tedlium $dl_dir
mv $dl_dir/TEDLIUM_release-3 $dl_dir/tedlium3
fi
# If you have pre-downloaded it to /path/to/musan,
# you can create a symlink
#
#ln -sfv /path/to/musan $dl_dir/musan
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 tedlium3 manifest"
# We assume that you have downloaded the tedlium3 corpus
# to $dl_dir/tedlium3
mkdir -p data/manifests
lhotse prepare tedlium $dl_dir/tedlium3 data/manifests
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 data/musan
mkdir -p data/manifests
lhotse prepare musan $dl_dir/musan data/manifests
fi
if [ $stage -le 3 ] && [ $stop_stage -ge 3 ]; then
log "Stage 3: Compute fbank for tedlium3"
mkdir -p data/fbank
./local/compute_fbank_tedlium.py
fi
if [ $stage -le 4 ] && [ $stop_stage -ge 4 ]; then
log "Stage 4: Compute fbank for musan"
mkdir -p data/fbank
./local/compute_fbank_musan.py
fi
if [ $stage -le 5 ] && [ $stop_stage -ge 5 ]; then
log "Stage 5: Prepare phone based lang"
lang_dir=data/lang_phone
mkdir -p $lang_dir
if [ ! -f $lang_dir/train.text ]; then
./local/prepare_transcripts.py \
--lang-dir $lang_dir \
--manifests-dir data/manifests
fi
if [ ! -f $lang_dir/lexicon_words.txt ]; then
./local/prepare_lexicon.py \
--lang-dir $lang_dir \
--manifests-dir data/manifests
fi
(echo '!SIL SIL'; echo '<UNK> <UNK>'; ) |
cat - $lang_dir/lexicon_words.txt |
sort | uniq > $lang_dir/lexicon.txt
if [ ! -f $lang_dir/L_disambig.pt ]; then
./local/prepare_lang.py --lang-dir $lang_dir
fi
fi
if [ $stage -le 6 ] && [ $stop_stage -ge 6 ]; then
log "Stage 6: Prepare BPE based lang"
for vocab_size in ${vocab_sizes[@]}; do
lang_dir=data/lang_bpe_${vocab_size}
mkdir -p $lang_dir
# We reuse words.txt from phone based lexicon
# so that the two can share G.pt later.
cp data/lang_phone/words.txt $lang_dir
if [ ! -f $lang_dir/transcript_words.txt ]; then
log "Generate data for BPE training"
cat data/lang_phone/train.text |
cut -d " " -f 2- > $lang_dir/transcript_words.txt
# remove the <unk> for transcript_words.txt
sed -i 's/ <unk>//g' $lang_dir/transcript_words.txt
sed -i 's/<unk> //g' $lang_dir/transcript_words.txt
sed -i 's/<unk>//g' $lang_dir/transcript_words.txt
fi
./local/train_bpe_model.py \
--lang-dir $lang_dir \
--vocab-size $vocab_size \
--transcript $lang_dir/transcript_words.txt
if [ ! -f $lang_dir/L_disambig.pt ]; then
./local/prepare_lang_bpe.py --lang-dir $lang_dir
fi
done
fi