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76 lines
2.5 KiB
76 lines
2.5 KiB
#!/bin/bash
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stage=0
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stop_stage=100
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export MAIN_ROOT=`realpath ${PWD}/../../../`
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if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
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# get durations from MFA's result
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echo "Generate durations.txt from MFA results ..."
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python3 ${MAIN_ROOT}/utils/gen_duration_from_textgrid.py \
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--inputdir=./aishell3_alignment_tone \
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--output durations.txt \
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--config=conf/default.yaml
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fi
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if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
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# extract features
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echo "Extract features ..."
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python3 ../preprocess.py \
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--dataset=aishell3 \
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--rootdir=~/datasets/data_aishell3/ \
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--dumpdir=dump \
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--dur-file=durations.txt \
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--config=conf/default.yaml \
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--num-cpu=20 \
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--cut-sil=True
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fi
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if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
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# get features' stats(mean and std)
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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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if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
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# normalize and covert phone/speaker to id, dev and test should use train's stats
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echo "Normalize ..."
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python3 ../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 ../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 ../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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