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110 lines
3.0 KiB
110 lines
3.0 KiB
2 years ago
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#!/bin/bash
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stage=-1
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stop_stage=100
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unit_type=char
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dict_dir=data/lang_char
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source ${MAIN_ROOT}/utils/parse_options.sh
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mkdir -p data
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mkdir -p ${dict_dir}
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TARGET_DIR=${MAIN_ROOT}/dataset
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mkdir -p ${TARGET_DIR}
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if [ ${stage} -le -1 ] && [ ${stop_stage} -ge -1 ]; then
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# download data, generate manifests
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python3 ${TARGET_DIR}/librispeech/librispeech.py \
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--manifest_prefix="data/manifest" \
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--target_dir="${TARGET_DIR}/librispeech" \
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--full_download="True"
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if [ $? -ne 0 ]; then
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echo "Prepare LibriSpeech failed. Terminated."
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exit 1
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fi
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for set in train-clean-100 train-clean-360 train-other-500 dev-clean dev-other test-clean test-other; do
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mv data/manifest.${set} data/manifest.${set}.raw
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done
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rm -rf data/manifest.train.raw data/manifest.dev.raw data/manifest.test.raw
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for set in train-clean-100 train-clean-360 train-other-500; do
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cat data/manifest.${set}.raw >> data/manifest.train.raw
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done
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for set in dev-clean dev-other; do
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cat data/manifest.${set}.raw >> data/manifest.dev.raw
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done
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for set in test-clean test-other; do
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cat data/manifest.${set}.raw >> data/manifest.test.raw
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done
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fi
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if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
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# compute mean and stddev for normalizer
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num_workers=$(nproc)
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python3 ${MAIN_ROOT}/utils/compute_mean_std.py \
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--manifest_path="data/manifest.train.raw" \
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--num_samples=2000 \
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--spectrum_type="fbank" \
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--feat_dim=161 \
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--delta_delta=false \
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--sample_rate=16000 \
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--stride_ms=10 \
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--window_ms=25 \
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--use_dB_normalization=False \
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--num_workers=${num_workers} \
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--output_path="data/mean_std.json"
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if [ $? -ne 0 ]; then
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echo "Compute mean and stddev failed. Terminated."
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exit 1
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fi
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fi
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if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
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# build vocabulary
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python3 ${MAIN_ROOT}/utils/build_vocab.py \
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--unit_type ${unit_type} \
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--count_threshold=0 \
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--vocab_path="${dict_dir}/vocab.txt" \
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--manifest_paths="data/manifest.train.raw"
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if [ $? -ne 0 ]; then
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echo "Build vocabulary failed. Terminated."
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exit 1
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fi
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fi
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if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
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# format manifest with tokenids, vocab size
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for set in train dev test dev-clean dev-other test-clean test-other; do
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{
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python3 ${MAIN_ROOT}/utils/format_data.py \
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--cmvn_path "data/mean_std.json" \
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--unit_type ${unit_type} \
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--vocab_path="${dict_dir}/vocab.txt" \
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--manifest_path="data/manifest.${set}.raw" \
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--output_path="data/manifest.${set}"
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if [ $? -ne 0 ]; then
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echo "Formt mnaifest.${set} failed. Terminated."
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exit 1
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fi
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}&
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done
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wait
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fi
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echo "LibriSpeech Data preparation done."
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if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
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mkdir -p exp/hubert
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echo "Pretrained hubert model download"
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wget -P exp/hubert https://paddlespeech.bj.bcebos.com/hubert/hubert-large-lv60.pdparams
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fi
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exit 0
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