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130 lines
3.4 KiB
130 lines
3.4 KiB
#!/bin/bash
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# Copyright 2021 Mobvoi Inc(Author: Di Wu, Binbin Zhang)
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# NPU, ASLP Group (Author: Qijie Shao)
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stage=-1
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stop_stage=100
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# Use your own data path. You need to download the WenetSpeech dataset by yourself.
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wenetspeech_data_dir=./wenetspeech
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# Make sure you have 1.2T for ${shards_dir}
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shards_dir=./wenetspeech_shards
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#wenetspeech training set
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set=L
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train_set=train_`echo $set | tr 'A-Z' 'a-z'`
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dev_set=dev
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test_sets="test_net test_meeting"
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cmvn=true
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cmvn_sampling_divisor=20 # 20 means 5% of the training data to estimate cmvn
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. ${MAIN_ROOT}/utils/parse_options.sh || exit 1;
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set -u
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set -o pipefail
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mkdir -p data
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TARGET_DIR=${MAIN_ROOT}/dataset
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mkdir -p ${TARGET_DIR}
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if [ ${stage} -le -2 ] && [ ${stop_stage} -ge -2 ]; then
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# download data
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echo "Please follow https://github.com/wenet-e2e/WenetSpeech to download the data."
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exit 0;
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fi
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if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
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echo "Data preparation"
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local/wenetspeech_data_prep.sh \
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--train-subset $set \
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$wenetspeech_data_dir \
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data || exit 1;
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fi
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if [ ${stage} -le -1 ] && [ ${stop_stage} -ge -1 ]; then
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# 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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# compute mean and stddev for normalizer
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if $cmvn; then
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full_size=`cat data/${train_set}/wav.scp | wc -l`
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sampling_size=$((full_size / cmvn_sampling_divisor))
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shuf -n $sampling_size data/$train_set/wav.scp \
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> data/$train_set/wav.scp.sampled
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num_workers=$(nproc)
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python3 ${MAIN_ROOT}/utils/compute_mean_std.py \
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--manifest_path="data/manifest.train.raw" \
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--spectrum_type="fbank" \
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--feat_dim=80 \
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--delta_delta=false \
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--stride_ms=10 \
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--window_ms=25 \
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--sample_rate=16000 \
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--use_dB_normalization=False \
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--num_samples=-1 \
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--num_workers=${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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fi
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dict=data/dict/lang_char.txt
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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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# 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/lang_char/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 dataset in train dev test; do
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{
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python3 ${MAIN_ROOT}/utils/format_data.py \
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--cmvn_path "data/mean_std.json" \
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--unit_type "char" \
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--vocab_path="data/vocab.txt" \
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--manifest_path="data/manifest.${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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