|
|
|
|
#!/bin/bash
|
|
|
|
|
|
|
|
|
|
config_path=$1
|
|
|
|
|
train_output_path=$2
|
|
|
|
|
ckpt_name=$3
|
|
|
|
|
|
|
|
|
|
stage=1
|
|
|
|
|
stop_stage=1
|
|
|
|
|
|
|
|
|
|
# use am to predict duration here
|
|
|
|
|
# 增加 am_phones_dict am_tones_dict 等，也可以用新的方式构造 am, 不需要这么多参数了就
|
|
|
|
|
|
|
|
|
|
# pwgan
|
|
|
|
|
if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
|
|
|
|
|
FLAGS_allocator_strategy=naive_best_fit \
|
|
|
|
|
FLAGS_fraction_of_gpu_memory_to_use=0.01 \
|
|
|
|
|
python3 ${BIN_DIR}/synthesize.py \
|
|
|
|
|
--erniesat_config=${config_path} \
|
|
|
|
|
--erniesat_ckpt=${train_output_path}/checkpoints/${ckpt_name} \
|
|
|
|
|
--erniesat_stat=dump/train/speech_stats.npy \
|
|
|
|
|
--voc=pwgan_vctk \
|
|
|
|
|
--voc_config=pwg_vctk_ckpt_0.1.1/default.yaml \
|
|
|
|
|
--voc_ckpt=pwg_vctk_ckpt_0.1.1/snapshot_iter_1500000.pdz \
|
|
|
|
|
--voc_stat=pwg_vctk_ckpt_0.1.1/feats_stats.npy \
|
|
|
|
|
--test_metadata=dump/test/norm/metadata.jsonl \
|
|
|
|
|
--output_dir=${train_output_path}/test \
|
|
|
|
|
--phones_dict=dump/phone_id_map.txt
|
|
|
|
|
fi
|
|
|
|
|
|
|
|
|
|
# hifigan
|
|
|
|
|
if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
|
|
|
|
|
FLAGS_allocator_strategy=naive_best_fit \
|
|
|
|
|
FLAGS_fraction_of_gpu_memory_to_use=0.01 \
|
|
|
|
|
python3 ${BIN_DIR}/synthesize.py \
|
|
|
|
|
--erniesat_config=${config_path} \
|
|
|
|
|
--erniesat_ckpt=${train_output_path}/checkpoints/${ckpt_name} \
|
|
|
|
|
--erniesat_stat=dump/train/speech_stats.npy \
|
|
|
|
|
--voc=hifigan_vctk \
|
|
|
|
|
--voc_config=hifigan_vctk_ckpt_0.2.0/default.yaml \
|
|
|
|
|
--voc_ckpt=hifigan_vctk_ckpt_0.2.0/snapshot_iter_2500000.pdz \
|
|
|
|
|
--voc_stat=hifigan_vctk_ckpt_0.2.0/feats_stats.npy \
|
|
|
|
|
--test_metadata=dump/test/norm/metadata.jsonl \
|
|
|
|
|
--output_dir=${train_output_path}/test \
|
|
|
|
|
--phones_dict=dump/phone_id_map.txt
|
|
|
|
|
fi
|
