#!/bin/bash stage=-1 stop_stage=100 dict_dir=data/lang_char . ${MAIN_ROOT}/utils/parse_options.sh || exit -1; mkdir -p data mkdir -p ${dict_dir} TARGET_DIR=${MAIN_ROOT}/examples/dataset mkdir -p ${TARGET_DIR} if [ ${stage} -le -1 ] && [ ${stop_stage} -ge -1 ]; then # download data, generate manifests python3 ${TARGET_DIR}/aishell/aishell.py \ --manifest_prefix="data/manifest" \ --target_dir="${TARGET_DIR}/aishell" if [ $? -ne 0 ]; then echo "Prepare Aishell failed. Terminated." exit 1 fi for dataset in train dev test; do mv data/manifest.${dataset} data/manifest.${dataset}.raw done fi if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then # compute mean and stddev for normalizer num_workers=$(nproc) python3 ${MAIN_ROOT}/utils/compute_mean_std.py \ --manifest_path="data/manifest.train.raw" \ --spectrum_type="linear" \ --delta_delta=false \ --stride_ms=10 \ --window_ms=20 \ --sample_rate=16000 \ --use_dB_normalization=True \ --num_samples=2000 \ --num_workers=${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 # download data, generate manifests # build vocabulary python3 ${MAIN_ROOT}/utils/build_vocab.py \ --unit_type="char" \ --count_threshold=0 \ --vocab_path="${dict_dir}/vocab.txt" \ --manifest_paths "data/manifest.train.raw" "data/manifest.dev.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 dataset in train dev test; do { python3 ${MAIN_ROOT}/utils/format_data.py \ --cmvn_path "data/mean_std.json" \ --unit_type "char" \ --vocab_path="${dict_dir}/vocab.txt" \ --manifest_path="data/manifest.${dataset}.raw" \ --output_path="data/manifest.${dataset}" if [ $? -ne 0 ]; then echo "Formt mnaifest failed. Terminated." exit 1 fi } & done wait fi echo "Aishell data preparation done." exit 0