data preparation for MLS

This commit is contained in:
marcoyang 2024-02-28 12:10:37 +08:00
parent 15e982aeba
commit ef2b95cb29
2 changed files with 103 additions and 112 deletions

View File

@ -61,7 +61,7 @@ def get_parser():
"--num-splits",
type=int,
required=True,
help="The number of splits of the XL subset",
help="The number of splits of the English subset",
)
parser.add_argument(
@ -111,12 +111,12 @@ def compute_fbank_mls_splits(args):
idx = f"{i}".zfill(num_digits)
logging.info(f"Processing {idx}/{num_splits}")
cuts_path = output_dir / f"cuts_{args.subset}.{idx}.jsonl.gz"
cuts_path = output_dir / f"mls-{args.language}_train.{idx}.jsonl.gz"
if cuts_path.is_file():
logging.info(f"{cuts_path} exists - skipping")
continue
raw_cuts_path = output_dir / f"cuts_{args.subset}_raw.{idx}.jsonl.gz"
raw_cuts_path = output_dir / f"mls-{args.language}_train_raw.{idx}.jsonl.gz"
logging.info(f"Loading {raw_cuts_path}")
cut_set = CutSet.from_file(raw_cuts_path)
@ -125,7 +125,7 @@ def compute_fbank_mls_splits(args):
cut_set = cut_set.compute_and_store_features_batch(
extractor=extractor,
storage_path=f"{output_dir}/feats_{args.subset}_{idx}",
storage_path=f"{output_dir}/feats_{args.language}_{idx}",
num_workers=args.num_workers,
batch_duration=args.batch_duration,
overwrite=True,

View File

@ -37,23 +37,9 @@ stop_stage=5
# - music
# - noise
# - speech
#
# lm directory is not necessary for transducer training with bpe units, but it
# is needed by phone based modeling, you can download it by running
# bash prepare.sh --stage -1 --stop-stage -1
# then you can see the following files in the directory.
# - $dl_dir/lm
# This directory contains the following files downloaded from
# http://www.openslr.org/resources/11
#
# - 3-gram.pruned.1e-7.arpa.gz
# - 3-gram.pruned.1e-7.arpa
# - 4-gram.arpa.gz
# - 4-gram.arpa
# - librispeech-vocab.txt
# - librispeech-lexicon.txt
# - librispeech-lm-norm.txt.gz
num_per_split=4000
fbank_dir=data/fbank_mls
dl_dir=$PWD/download
. shared/parse_options.sh || exit 1
@ -63,9 +49,9 @@ dl_dir=$PWD/download
# data/lang_bpe_yyy if the array contains xxx, yyy
vocab_sizes=(
# 5000
# 2000
# 1000
500
2000
1000
# 500
)
# All files generated by this script are saved in "data".
@ -81,17 +67,29 @@ log() {
log "Running prepare.sh"
log "dl_dir: $dl_dir"
log "fbank_dir: $fbank_dir"
languages=(
english
german
dutch
spanish
italian
french
polish
portuguese
)
if [ $stage -le 0 ] && [ $stop_stage -ge 0 ]; then
log "Stage 0: Download data"
# If you have pre-downloaded it to /path/to/LibriSpeech,
# If you have pre-downloaded it to /path/to/MLS,
# you can create a symlink
#
# ln -sfv /path/to/LibriSpeech $dl_dir/LibriSpeech
# ln -sfv /path/to/MLS $dl_dir/MLS
#
if [ ! -d $dl_dir/LibriSpeech/train-other-500 ]; then
lhotse download librispeech --full $dl_dir
if [ ! -d $dl_dir/MLS/train-other-500 ]; then
lhotse download mls --full $dl_dir
fi
# If you have pre-downloaded it to /path/to/musan,
@ -105,13 +103,13 @@ if [ $stage -le 0 ] && [ $stop_stage -ge 0 ]; then
fi
if [ $stage -le 1 ] && [ $stop_stage -ge 1 ]; then
log "Stage 1: Prepare LibriSpeech manifest"
# We assume that you have downloaded the LibriSpeech corpus
# to $dl_dir/LibriSpeech
log "Stage 1: Prepare MLS manifest"
# We assume that you have downloaded the MLS corpus
# to $dl_dir/MLS
mkdir -p data/manifests
if [ ! -e data/manifests/.librispeech.done ]; then
lhotse prepare librispeech -j $nj $dl_dir/LibriSpeech data/manifests
touch data/manifests/.librispeech.done
if [ ! -e data/manifests/.mls.done ]; then
lhotse prepare mls -j $nj $dl_dir/MLS data/manifests
touch data/manifests/.mls.done
fi
fi
@ -127,50 +125,73 @@ if [ $stage -le 2 ] && [ $stop_stage -ge 2 ]; then
fi
if [ $stage -le 3 ] && [ $stop_stage -ge 3 ]; then
log "Stage 3: Compute fbank for librispeech"
mkdir -p data/fbank
if [ ! -e data/fbank/.librispeech.done ]; then
./local/compute_fbank_librispeech.py
touch data/fbank/.librispeech.done
fi
if [ ! -f data/fbank/librispeech_cuts_train-all-shuf.jsonl.gz ]; then
cat <(gunzip -c data/fbank/librispeech_cuts_train-clean-100.jsonl.gz) \
<(gunzip -c data/fbank/librispeech_cuts_train-clean-360.jsonl.gz) \
<(gunzip -c data/fbank/librispeech_cuts_train-other-500.jsonl.gz) | \
shuf | gzip -c > data/fbank/librispeech_cuts_train-all-shuf.jsonl.gz
fi
if [ ! -e data/fbank/.librispeech-validated.done ]; then
log "Validating data/fbank for LibriSpeech"
parts=(
train-clean-100
train-clean-360
train-other-500
test-clean
test-other
dev-clean
dev-other
)
for part in ${parts[@]}; do
python3 ./local/validate_manifest.py \
data/fbank/librispeech_cuts_${part}.jsonl.gz
done
touch data/fbank/.librispeech-validated.done
log "Stage 3: Split english subset into pieces (may take 30 minutes)"
split_dir=${fbank_dir}/english_split
if [ ! -f $split_dir/.split_completed ]; then
lhotse split-lazy ${fbank_dir}/mls-english_train_raw.jsonl.gz $split_dir $num_per_split
touch $split_dir/.split_completed
fi
fi
if [ $stage -le 4 ] && [ $stop_stage -ge 4 ]; then
log "Stage 4: Compute fbank for musan"
mkdir -p data/fbank
if [ ! -e data/fbank/.musan.done ]; then
./local/compute_fbank_musan.py
touch data/fbank/.musan.done
log "Stage 4: Compute fbank for MLS (except English)"
mkdir -p ${fbank_dir}
if [ ! -e ${fbank_dir}/.mls.done ]; then
./local/compute_fbank_mls.py
touch ${fbank_dir}/.mls.done
fi
fi
if [ $stage -le 5 ] && [ $stop_stage -ge 5 ]; then
log "Stage 5: Prepare BPE based lang"
log "Stage 5: Compute fbank for English split of MLS"
if [ ! -e ${fbank_dir}/.mls-english.done ]; then
num_splits=$(find ${fbank_dir}/english_split -name "mls-english_train_raw.*.jsonl.gz" | wc -l)
./local/compute_fbank_mls_splits.py \
--fbank-dir $fbank_dir \
--num-workers 20 \
--language english \
--num-splits $num_splits \
touch ${fbank_dir}/.mls-english.done
fi
if [ ! -e ${fbank_dir}/mls-english_train.jsonl.gz ]; then
pieces=$(find ${fbank_dir}/english_split -name "mls-english_train.*.jsonl.gz")
lhotse combine $pieces ${fbank_dir}/mls-english_train.jsonl.gz
fi
fi
if [ $stage -le 6 ] && [ $stop_stage -ge 6 ]; then
log "Stage 6: Validate the manifest of MLS"
if [ ! -e ${fbank_dir}/.mls-validated.done ]; then
log "Validating the fbank features for MLS"
parts=(
train
dev
test
)
for lan in ${languages[@]}; do
for part in ${parts[@]}; do
python3 ./local/validate_manifest.py \
${fbank_dir}/mls-${lan}_${part}.jsonl.gz
done
done
touch ${fbank_dir}/.mls-validated.done
fi
fi
if [ $stage -le 7 ] && [ $stop_stage -ge 7 ]; then
log "Stage 7: Compute fbank for musan"
mkdir -p ${fbank_dir}
if [ ! -e ${fbank_dir}/.musan.done ]; then
./local/compute_fbank_musan.py
touch ${fbank_dir}/.musan.done
fi
fi
if [ $stage -le 8 ] && [ $stop_stage -ge 8 ]; then
log "Stage 8: Prepare BPE based lang"
for vocab_size in ${vocab_sizes[@]}; do
lang_dir=data/lang_bpe_${vocab_size}
@ -178,13 +199,18 @@ if [ $stage -le 5 ] && [ $stop_stage -ge 5 ]; then
if [ ! -f $lang_dir/transcript_words.txt ]; then
log "Generate data for BPE training"
files=$(
find "$dl_dir/LibriSpeech/train-clean-100" -name "*.trans.txt"
find "$dl_dir/LibriSpeech/train-clean-360" -name "*.trans.txt"
find "$dl_dir/LibriSpeech/train-other-500" -name "*.trans.txt"
files=(
"$dl_dir/MLS/mls_english/train/transcripts.txt"
"$dl_dir/MLS/mls_german/train/transcripts.txt"
"$dl_dir/MLS/mls_dutch/train/transcripts.txt"
"$dl_dir/MLS/mls_french/train/transcripts.txt"
"$dl_dir/MLS/mls_spanish/train/transcripts.txt"
"$dl_dir/MLS/mls_italian/train/transcripts.txt"
"$dl_dir/MLS/mls_portuguese/train/transcripts.txt"
"$dl_dir/MLS/mls_polish/train/transcripts.txt"
)
for f in ${files[@]}; do
cat $f | cut -d " " -f 2-
head -n 1000000 $f | cut -d " " -f 2-
done > $lang_dir/transcript_words.txt
fi
@ -192,45 +218,10 @@ if [ $stage -le 5 ] && [ $stop_stage -ge 5 ]; then
./local/train_bpe_model.py \
--lang-dir $lang_dir \
--vocab-size $vocab_size \
--transcript $lang_dir/transcript_words.txt
--character-coverage 0.999 \
--transcript $lang_dir/transcript_words.txt \
--byte-fallback
fi
done
fi
if [ $stage -le 6 ] && [ $stop_stage -ge 6 ]; then
log "Stage 6: Prepare phone based lang"
lang_dir=data/lang_phone
mkdir -p $lang_dir
if [ ! -f $dl_dir/lm/librispeech-lexicon.txt ]; then
log "No lexicon file in $dl_dir/lm, please run :"
log "prepare.sh --stage -1 --stop-stage -1"
exit -1
fi
if [ ! -f $lang_dir/lexicon.txt ]; then
(echo '!SIL SIL'; echo '<SPOKEN_NOISE> SPN'; echo '<UNK> SPN'; ) |
cat - $dl_dir/lm/librispeech-lexicon.txt |
sort | uniq > $lang_dir/lexicon.txt
fi
if [ ! -f $lang_dir/L_disambig.pt ]; then
./local/prepare_lang.py --lang-dir $lang_dir
fi
if [ ! -f $lang_dir/L.fst ]; then
log "Converting L.pt to L.fst"
./shared/convert-k2-to-openfst.py \
--olabels aux_labels \
$lang_dir/L.pt \
$lang_dir/L.fst
fi
if [ ! -f $lang_dir/L_disambig.fst ]; then
log "Converting L_disambig.pt to L_disambig.fst"
./shared/convert-k2-to-openfst.py \
--olabels aux_labels \
$lang_dir/L_disambig.pt \
$lang_dir/L_disambig.fst
fi
fi