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89 lines
2.3 KiB
89 lines
2.3 KiB
#!/bin/bash
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stage=-1
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stop_stage=100
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source ${MAIN_ROOT}/utils/parse_options.sh
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mkdir -p data
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TARGET_DIR=${MAIN_ROOT}/examples/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 ${TARGET_DIR}/aishell/aishell.py \
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--manifest_prefix="data/manifest" \
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--target_dir="${TARGET_DIR}/aishell"
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if [ $? -ne 0 ]; then
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echo "Prepare Aishell failed. Terminated."
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exit 1
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fi
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for dataset in train dev test; do
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mv data/manifest.${dataset} data/manifest.${dataset}.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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# download data, generate manifests
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# build vocabulary
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python3 ${MAIN_ROOT}/utils/build_vocab.py \
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--unit_type="char" \
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--count_threshold=0 \
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--vocab_path="data/vocab.txt" \
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--manifest_paths "data/manifest.train.raw" "data/manifest.dev.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 1 ] && [ ${stop_stage} -ge 1 ]; then
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# compute mean and stddev for normalizer
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num_workers=$(nproc)
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python3 ${MAIN_ROOT}/utils/compute_mean_std.py \
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--manifest_path="data/manifest.train.raw" \
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--specgram_type="linear" \
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--delta_delta=false \
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--stride_ms=10.0 \
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--window_ms=20.0 \
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--sample_rate=16000 \
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--use_dB_normalization=True \
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--num_samples=2000 \
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--num_workers=${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 2 ] && [ ${stop_stage} -ge 2 ]; then
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# format manifest with tokenids, vocab size
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for dataset in train dev test; do
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{
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python3 ${MAIN_ROOT}/utils/format_data.py \
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--feat_type "raw" \
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--cmvn_path "data/mean_std.json" \
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--unit_type "char" \
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--vocab_path="data/vocab.txt" \
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--manifest_path="data/manifest.${dataset}.raw" \
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--output_path="data/manifest.${dataset}"
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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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fi
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echo "Aishell data preparation done."
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exit 0
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