#!/bin/bash stage=0 stop_stage=100 config_path=$1 datasets_root_dir=$2 mfa_root_dir=$3 # 1. get durations from MFA's result if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then echo "Generate durations_baker.txt from MFA results ..." python3 ${MAIN_ROOT}/utils/gen_duration_from_textgrid.py \ --inputdir=${mfa_root_dir}/baker_alignment_tone \ --output durations_baker.txt \ --config=${config_path} fi if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then echo "Generate durations_ljspeech.txt from MFA results ..." python3 ${MAIN_ROOT}/utils/gen_duration_from_textgrid.py \ --inputdir=${mfa_root_dir}/ljspeech_alignment \ --output durations_ljspeech.txt \ --config=${config_path} fi if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then echo "Generate durations_aishell3.txt from MFA results ..." python3 ${MAIN_ROOT}/utils/gen_duration_from_textgrid.py \ --inputdir=${mfa_root_dir}/aishell3_alignment_tone \ --output durations_aishell3.txt \ --config=${config_path} fi if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then echo "Generate durations_vctk.txt from MFA results ..." python3 ${MAIN_ROOT}/utils/gen_duration_from_textgrid.py \ --inputdir=${mfa_root_dir}/vctk_alignment \ --output durations_vctk.txt \ --config=${config_path} fi if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then # concat duration file echo "concat durations_baker.txt, durations_ljspeech.txt, durations_aishell3.txt and durations_vctk.txt to durations.txt" cat durations_baker.txt durations_ljspeech.txt durations_aishell3.txt durations_vctk.txt > durations.txt fi # 2. extract features if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then echo "Extract baker features ..." python3 ${BIN_DIR}/preprocess.py \ --dataset=baker \ --rootdir=${datasets_root_dir}/BZNSYP/ \ --dumpdir=dump \ --dur-file=durations.txt \ --config=${config_path} \ --num-cpu=20 \ --cut-sil=True \ --write_metadata_method=a fi if [ ${stage} -le 6 ] && [ ${stop_stage} -ge 6 ]; then echo "Extract ljspeech features ..." python3 ${BIN_DIR}/preprocess.py \ --dataset=ljspeech \ --rootdir=${datasets_root_dir}/LJSpeech-1.1/ \ --dumpdir=dump \ --dur-file=durations.txt \ --config=${config_path} \ --num-cpu=20 \ --cut-sil=True \ --write_metadata_method=a fi if [ ${stage} -le 7 ] && [ ${stop_stage} -ge 7 ]; then echo "Extract aishell3 features ..." python3 ${BIN_DIR}/preprocess.py \ --dataset=aishell3 \ --rootdir=${datasets_root_dir}/data_aishell3/ \ --dumpdir=dump \ --dur-file=durations.txt \ --config=${config_path} \ --num-cpu=20 \ --cut-sil=True \ --write_metadata_method=a fi if [ ${stage} -le 8 ] && [ ${stop_stage} -ge 8 ]; then echo "Extract vctk features ..." python3 ${BIN_DIR}/preprocess.py \ --dataset=vctk \ --rootdir=${datasets_root_dir}/VCTK-Corpus-0.92/ \ --dumpdir=dump \ --dur-file=durations.txt \ --config=${config_path} \ --num-cpu=20 \ --cut-sil=True \ --write_metadata_method=a fi # 3. get features' stats(mean and std) if [ ${stage} -le 9 ] && [ ${stop_stage} -ge 9 ]; then echo "Get features' stats ..." python3 ${MAIN_ROOT}/utils/compute_statistics.py \ --metadata=dump/train/raw/metadata.jsonl \ --field-name="speech" python3 ${MAIN_ROOT}/utils/compute_statistics.py \ --metadata=dump/train/raw/metadata.jsonl \ --field-name="pitch" python3 ${MAIN_ROOT}/utils/compute_statistics.py \ --metadata=dump/train/raw/metadata.jsonl \ --field-name="energy" fi # 4. normalize and covert phone/speaker to id, dev and test should use train's stats if [ ${stage} -le 10 ] && [ ${stop_stage} -ge 10 ]; then echo "Normalize ..." python3 ${BIN_DIR}/normalize.py \ --metadata=dump/train/raw/metadata.jsonl \ --dumpdir=dump/train/norm \ --speech-stats=dump/train/speech_stats.npy \ --pitch-stats=dump/train/pitch_stats.npy \ --energy-stats=dump/train/energy_stats.npy \ --phones-dict=dump/phone_id_map.txt \ --speaker-dict=dump/speaker_id_map.txt python3 ${BIN_DIR}/normalize.py \ --metadata=dump/dev/raw/metadata.jsonl \ --dumpdir=dump/dev/norm \ --speech-stats=dump/train/speech_stats.npy \ --pitch-stats=dump/train/pitch_stats.npy \ --energy-stats=dump/train/energy_stats.npy \ --phones-dict=dump/phone_id_map.txt \ --speaker-dict=dump/speaker_id_map.txt python3 ${BIN_DIR}/normalize.py \ --metadata=dump/test/raw/metadata.jsonl \ --dumpdir=dump/test/norm \ --speech-stats=dump/train/speech_stats.npy \ --pitch-stats=dump/train/pitch_stats.npy \ --energy-stats=dump/train/energy_stats.npy \ --phones-dict=dump/phone_id_map.txt \ --speaker-dict=dump/speaker_id_map.txt fi