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