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PaddleSpeech/examples/other/tts_finetune/tts3/run_en.sh

107 lines
3.1 KiB

#!/bin/bash
set -e
source path.sh
input_dir=./input/ljspeech_mini
newdir_name="newdir"
new_dir=${input_dir}/${newdir_name}
pretrained_model_dir=./pretrained_models/fastspeech2_vctk_ckpt_1.2.0
mfa_dir=./mfa_result
dump_dir=./dump
output_dir=./exp/default
lang=en
ngpu=1
finetune_config=./conf/finetune.yaml
replace_spkid=0
ckpt=snapshot_iter_66300
gpus=1
CUDA_VISIBLE_DEVICES=${gpus}
stage=0
stop_stage=100
# with the following command, you can choose the stage range you want to run
# such as `./run.sh --stage 0 --stop-stage 0`
# this can not be mixed use with `$1`, `$2` ...
source ${MAIN_ROOT}/utils/parse_options.sh || exit 1
# check oov
if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
echo "check oov"
python3 local/check_oov.py \
--input_dir=${input_dir} \
--pretrained_model_dir=${pretrained_model_dir} \
--newdir_name=${newdir_name} \
--lang=${lang}
fi
# get mfa result
if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
echo "get mfa result"
python3 local/get_mfa_result.py \
--input_dir=${new_dir} \
--mfa_dir=${mfa_dir} \
--lang=${lang}
fi
# generate durations.txt
if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
echo "generate durations.txt"
python3 local/generate_duration.py \
--mfa_dir=${mfa_dir}
fi
# extract feature
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
echo "extract feature"
python3 local/extract_feature.py \
--duration_file="./durations.txt" \
--input_dir=${new_dir} \
--dump_dir=${dump_dir} \
--pretrained_model_dir=${pretrained_model_dir} \
--replace_spkid=$replace_spkid
fi
# create finetune env
if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
echo "create finetune env"
python3 local/prepare_env.py \
--pretrained_model_dir=${pretrained_model_dir} \
--output_dir=${output_dir}
fi
# finetune
if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then
echo "finetune..."
python3 local/finetune.py \
--pretrained_model_dir=${pretrained_model_dir} \
--dump_dir=${dump_dir} \
--output_dir=${output_dir} \
--ngpu=${ngpu} \
--epoch=100 \
--finetune_config=${finetune_config}
fi
# synthesize e2e
if [ ${stage} -le 6 ] && [ ${stop_stage} -ge 6 ]; then
echo "in hifigan syn_e2e"
python3 ${BIN_DIR}/../synthesize_e2e.py \
--am=fastspeech2_vctk \
--am_config=${pretrained_model_dir}/default.yaml \
--am_ckpt=${output_dir}/checkpoints/${ckpt}.pdz \
--am_stat=${pretrained_model_dir}/speech_stats.npy \
--voc=hifigan_vctk \
--voc_config=pretrained_models/hifigan_vctk_ckpt_0.2.0/default.yaml \
--voc_ckpt=pretrained_models/hifigan_vctk_ckpt_0.2.0/snapshot_iter_2500000.pdz \
--voc_stat=pretrained_models/hifigan_vctk_ckpt_0.2.0/feats_stats.npy \
--lang=en \
--text=${BIN_DIR}/../../assets/sentences_en.txt \
--output_dir=./test_e2e/ \
--phones_dict=${dump_dir}/phone_id_map.txt \
--speaker_dict=${dump_dir}/speaker_id_map.txt \
--spk_id=$replace_spkid
fi