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

86 lines
2.1 KiB

#!/bin/bash
stage=-1
stop_stage=100
unit_type=word
TIMIT_path=
source ${MAIN_ROOT}/utils/parse_options.sh
mkdir -p data
TARGET_DIR=${MAIN_ROOT}/examples/dataset
mkdir -p ${TARGET_DIR}
if [ ${stage} -le -1 ] && [ ${stop_stage} -ge -1 ]; then
# download data, generate manifests
python3 ${TARGET_DIR}/timit/timit_kaldi_standard_split.py \
--manifest_prefix="data/manifest" \
--src="data/local" \
if [ $? -ne 0 ]; then
echo "Prepare TIMIT failed. Terminated."
exit 1
fi
fi
if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
# compute mean and stddev for normalizer
num_workers=$(nproc)
python3 ${MAIN_ROOT}/utils/compute_mean_std.py \
--manifest_path="data/manifest.train.raw" \
--num_samples=-1 \
--spectrum_type="fbank" \
--feat_dim=80 \
--delta_delta=false \
--sample_rate=16000 \
--stride_ms=10 \
--window_ms=25 \
--use_dB_normalization=False \
--num_workers=${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 ${unit_type} \
--count_threshold=0 \
--vocab_path="data/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 set in train dev test; do
{
python3 ${MAIN_ROOT}/utils/format_data.py \
--cmvn_path "data/mean_std.json" \
--unit_type ${unit_type} \
--vocab_path="data/vocab.txt" \
--manifest_path="data/manifest.${set}.raw" \
--output_path="data/manifest.${set}"
if [ $? -ne 0 ]; then
echo "Formt mnaifest.${set} failed. Terminated."
exit 1
fi
}&
done
wait
fi
echo "TIMIT Data preparation done."
exit 0