#!/bin/bash stage=0 stop_stage=100 config_path=$1 add_blank=$2 # copy from tts3/preprocess if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then # get durations from MFA's result echo "Generate durations.txt from MFA results ..." python3 ${MAIN_ROOT}/utils/gen_duration_from_textgrid.py \ --inputdir=./aishell3_alignment_tone \ --output durations.txt \ --config=${config_path} fi if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then # extract features echo "Extract features ..." python3 ${BIN_DIR}/preprocess.py \ --dataset=aishell3 \ --rootdir=~/datasets/data_aishell3/ \ --dumpdir=dump \ --dur-file=durations.txt \ --config=${config_path} \ --num-cpu=20 \ --cut-sil=True fi if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then # get features' stats(mean and std) echo "Get features' stats ..." python3 ${MAIN_ROOT}/utils/compute_statistics.py \ --metadata=dump/train/raw/metadata.jsonl \ --field-name="feats" fi if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then # normalize and covert phone/speaker to id, dev and test should use train's stats echo "Normalize ..." python3 ${BIN_DIR}/normalize.py \ --metadata=dump/train/raw/metadata.jsonl \ --dumpdir=dump/train/norm \ --feats-stats=dump/train/feats_stats.npy \ --phones-dict=dump/phone_id_map.txt \ --speaker-dict=dump/speaker_id_map.txt \ --add-blank=${add_blank} \ --skip-wav-copy python3 ${BIN_DIR}/normalize.py \ --metadata=dump/dev/raw/metadata.jsonl \ --dumpdir=dump/dev/norm \ --feats-stats=dump/train/feats_stats.npy \ --phones-dict=dump/phone_id_map.txt \ --speaker-dict=dump/speaker_id_map.txt \ --add-blank=${add_blank} \ --skip-wav-copy python3 ${BIN_DIR}/normalize.py \ --metadata=dump/test/raw/metadata.jsonl \ --dumpdir=dump/test/norm \ --feats-stats=dump/train/feats_stats.npy \ --phones-dict=dump/phone_id_map.txt \ --speaker-dict=dump/speaker_id_map.txt \ --add-blank=${add_blank} \ --skip-wav-copy fi