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PaddleSpeech/examples/librispeech/asr1/local/data.sh

126 lines
3.4 KiB

#!/bin/bash
stage=-1
stop_stage=100
dict_dir=data/lang_char
# bpemode (unigram or bpe)
nbpe=5000
bpemode=unigram
bpeprefix="${dict_dir}/bpe_${bpemode}_${nbpe}"
stride_ms=10
window_ms=25
sample_rate=16000
feat_dim=80
source ${MAIN_ROOT}/utils/parse_options.sh
mkdir -p data
mkdir -p ${dict_dir}
TARGET_DIR=${MAIN_ROOT}/examples/dataset
mkdir -p ${TARGET_DIR}
if [ ${stage} -le -1 ] && [ ${stop_stage} -ge -1 ]; then
# download data, generate manifests
python3 ${TARGET_DIR}/librispeech/librispeech.py \
--manifest_prefix="data/manifest" \
--target_dir="${TARGET_DIR}/librispeech" \
--full_download="True"
if [ $? -ne 0 ]; then
echo "Prepare LibriSpeech failed. Terminated."
exit 1
fi
for sub in train-clean-100 train-clean-360 train-other-500 dev-clean dev-other test-clean test-other; do
mv data/manifest.${sub} data/manifest.${sub}.raw
done
rm -rf data/manifest.train.raw data/manifest.dev.raw data/manifest.test.raw
for sub in train-clean-100 train-clean-360 train-other-500; do
cat data/manifest.${sub}.raw >> data/manifest.train.raw
done
for sub in dev-clean dev-other; do
cat data/manifest.${sub}.raw >> data/manifest.dev.raw
done
for sub in test-clean test-other; do
cat data/manifest.${sub}.raw >> data/manifest.test.raw
done
fi
if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
# compute mean and stddev for normalizer
num_workers=$(nproc)
python3 ${MAIN_ROOT}/utils/compute_mean_std.py \
--manifest_path="data/manifest.train.raw" \
--num_samples=-1 \
--spectrum_type="fbank" \
--feat_dim=${feat_dim} \
--delta_delta=false \
--sample_rate=${sample_rate} \
--stride_ms=${stride_ms} \
--window_ms=${window_ms} \
--use_dB_normalization=False \
--num_workers=${num_workers} \
--output_path="data/mean_std.json"
if [ $? -ne 0 ]; then
echo "Compute mean and stddev failed. Terminated."
exit 1
fi
fi
if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
# build vocabulary
python3 ${MAIN_ROOT}/utils/build_vocab.py \
--unit_type "spm" \
--spm_vocab_size=${nbpe} \
--spm_mode ${bpemode} \
--spm_model_prefix ${bpeprefix} \
--vocab_path="${dict_dir}/vocab.txt" \
--manifest_paths="data/manifest.train.raw"
if [ $? -ne 0 ]; then
echo "Build vocabulary failed. Terminated."
exit 1
fi
fi
if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
# format manifest with tokenids, vocab size
for sub in train dev test dev-clean dev-other test-clean test-other; do
{
python3 ${MAIN_ROOT}/utils/format_data.py \
--cmvn_path "data/mean_std.json" \
--unit_type "spm" \
--spm_model_prefix ${bpeprefix} \
--vocab_path="${dict_dir}/vocab.txt" \
--manifest_path="data/manifest.${sub}.raw" \
--output_path="data/manifest.${sub}"
if [ $? -ne 0 ]; then
echo "Formt mnaifest failed. Terminated."
exit 1
fi
}&
done
wait
for sub in train dev; do
mv data/manifest.${sub} data/manifest.${sub}.fmt
done
fi
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
for sub in train dev; do
remove_longshortdata.py --maxframes 3000 --maxchars 400 --stride_ms ${stride_ms} data/manifest.${sub}.fmt data/manifest.${sub}
done
fi
echo "LibriSpeech Data preparation done."
exit 0