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126 lines
3.4 KiB
126 lines
3.4 KiB
#!/bin/bash
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stage=-1
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stop_stage=100
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dict_dir=data/lang_char
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# bpemode (unigram or bpe)
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nbpe=5000
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bpemode=unigram
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bpeprefix="${dict_dir}/bpe_${bpemode}_${nbpe}"
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stride_ms=10
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window_ms=25
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sample_rate=16000
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feat_dim=80
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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 [ $? -ne 0 ]; then
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echo "Prepare LibriSpeech failed. Terminated."
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exit 1
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fi
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for sub in train-clean-100 train-clean-360 train-other-500 dev-clean dev-other test-clean test-other; do
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mv data/manifest.${sub} data/manifest.${sub}.raw
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done
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rm -rf data/manifest.train.raw data/manifest.dev.raw data/manifest.test.raw
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for sub in train-clean-100 train-clean-360 train-other-500; do
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cat data/manifest.${sub}.raw >> data/manifest.train.raw
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done
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for sub in dev-clean dev-other; do
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cat data/manifest.${sub}.raw >> data/manifest.dev.raw
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done
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for sub in test-clean test-other; do
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cat data/manifest.${sub}.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 ${MAIN_ROOT}/utils/compute_mean_std.py \
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--manifest_path="data/manifest.train.raw" \
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--num_samples=-1 \
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--spectrum_type="fbank" \
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--feat_dim=${feat_dim} \
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--delta_delta=false \
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--sample_rate=${sample_rate} \
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--stride_ms=${stride_ms} \
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--window_ms=${window_ms} \
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--use_dB_normalization=False \
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--num_workers=${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 ${MAIN_ROOT}/utils/build_vocab.py \
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--unit_type "spm" \
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--spm_vocab_size=${nbpe} \
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--spm_mode ${bpemode} \
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--spm_model_prefix ${bpeprefix} \
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--vocab_path="${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 sub 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 "spm" \
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--spm_model_prefix ${bpeprefix} \
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--vocab_path="${dict_dir}/vocab.txt" \
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--manifest_path="data/manifest.${sub}.raw" \
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--output_path="data/manifest.${sub}"
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if [ $? -ne 0 ]; then
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echo "Formt mnaifest failed. Terminated."
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exit 1
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fi
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}&
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done
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wait
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for sub in train dev; do
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mv data/manifest.${sub} data/manifest.${sub}.fmt
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done
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fi
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if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
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for sub in train dev; do
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remove_longshortdata.py --maxframes 3000 --maxchars 400 --stride_ms ${stride_ms} data/manifest.${sub}.fmt data/manifest.${sub}
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done
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fi
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echo "LibriSpeech Data preparation done."
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exit 0
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