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Merge branch 'PaddlePaddle:develop' into develop

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Echo-Nie 5 months ago committed by GitHub
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8
examples/csmsc/tts3/README.md
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@ -107,8 +107,10 @@ pwg_baker_ckpt_0.4
```
`./local/synthesize.sh` calls `${BIN_DIR}/../synthesize.py`, which can synthesize waveform from `metadata.jsonl`.
```bash
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name}
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name}
```
`--stage` controls the vocoder model during synthesis. The parameter values range from `0-4`, corresponding to the following five vocoder models: `pwgan`, `multi band melgan`, `style melgan`, `hifigan`, and `wavernn`.
```text
usage: synthesize.py [-h]
[--am {speedyspeech_csmsc,fastspeech2_csmsc,fastspeech2_ljspeech,fastspeech2_aishell3,fastspeech2_vctk,tacotron2_csmsc,tacotron2_ljspeech,tacotron2_aishell3}]
@ -155,8 +157,10 @@ optional arguments:
```
`./local/synthesize_e2e.sh` calls `${BIN_DIR}/../synthesize_e2e.py`, which can synthesize waveform from text file.
```bash
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name}
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name}
```
`--stage` controls the vocoder model during synthesis. The parameter values are {`0,1,3,4`}, corresponding to the following four vocoder models: `pwgan`, `multi band melgan`, `hifigan`, and `wavernn`.
```text
usage: synthesize_e2e.py [-h]
[--am {speedyspeech_csmsc,speedyspeech_aishell3,fastspeech2_csmsc,fastspeech2_ljspeech,fastspeech2_aishell3,fastspeech2_vctk,tacotron2_csmsc,tacotron2_ljspeech}]

8
examples/csmsc/tts3/README_cn.md
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@ -113,8 +113,10 @@ pwg_baker_ckpt_0.4
`./local/synthesize.sh` 调用 `${BIN_DIR}/../synthesize.py` 即可从 `metadata.jsonl`中合成波形。
```bash
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name}
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name}
```
`--stage` 参数用于控制合成过程中使用的声码器模型。该参数的取值范围为 `0-4`，分别对应以下五种声码器模型：`pwgan`、`multi band melgan`、`style melgan`、`hifigan` 和 `wavernn`。
```text
usage: synthesize.py [-h]
[--am {speedyspeech_csmsc,fastspeech2_csmsc,fastspeech2_ljspeech,fastspeech2_aishell3,fastspeech2_vctk,tacotron2_csmsc,tacotron2_ljspeech,tacotron2_aishell3}]
@ -162,8 +164,10 @@ optional arguments:
`./local/synthesize_e2e.sh` 调用 `${BIN_DIR}/../synthesize_e2e.py`，即可从文本文件中合成波形。
```bash
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name}
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name}
```
`--stage` 参数用于控制合成过程中使用的声码器模型。该参数的取值范围为{ `0,1,3,4`}，分别对应以下四种声码器模型：`pwgan`、`multi band melgan`、`hifigan` 和 `wavernn`。
```text
usage: synthesize_e2e.py [-h]
[--am {speedyspeech_csmsc,speedyspeech_aishell3,fastspeech2_csmsc,fastspeech2_ljspeech,fastspeech2_aishell3,fastspeech2_vctk,tacotron2_csmsc,tacotron2_ljspeech}]

10
examples/csmsc/tts3/run.sh
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@ -27,13 +27,15 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
fi
if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
# synthesize, vocoder is pwgan by default
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1
# synthesize, vocoder is pwgan by default stage 0
# use stage 1-4 to select the vocoder to use {multi band melgan, style melgan, hifigan, wavernn}
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} || exit -1
fi
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
# synthesize_e2e, vocoder is pwgan by default
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1
# synthesize_e2e, vocoder is pwgan by default stage 0
# use stage 1,3,4 to select the vocoder to use {multi band melgan, hifigan, wavernn}
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} || exit -1
fi
if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then

12
examples/csmsc/voc3/local/synthesize_e2e.sh
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@ -8,13 +8,13 @@ FLAGS_allocator_strategy=naive_best_fit \
FLAGS_fraction_of_gpu_memory_to_use=0.01 \
python3 ${BIN_DIR}/../../synthesize_e2e.py \
--am=fastspeech2_csmsc \
--am_config=${config_path} \
--am_ckpt=${train_output_path}/checkpoints/${ckpt_name} \
--am_stat=dump/train/speech_stats.npy \
--am_config=fastspeech2_nosil_baker_ckpt_0.4/default.yaml \
--am_ckpt=fastspeech2_nosil_baker_ckpt_0.4/snapshot_iter_76000.pdz \
--am_stat=fastspeech2_nosil_baker_ckpt_0.4/speech_stats.npy \
--voc=mb_melgan_csmsc \
--voc_config=mb_melgan_csmsc_ckpt_0.1.1/default.yaml \
--voc_ckpt=mb_melgan_csmsc_ckpt_0.1.1/snapshot_iter_1000000.pdz\
--voc_stat=mb_melgan_csmsc_ckpt_0.1.1/feats_stats.npy \
--voc_config=${config_path} \
--voc_ckpt=${train_output_path}/checkpoints/${ckpt_name} \
--voc_stat=dump/train/feats_stats.npy \
--lang=zh \
--text=${BIN_DIR}/../../assets/sentences.txt \
--output_dir=${train_output_path}/test_e2e \

12
examples/csmsc/voc5/local/synthesize_e2e.sh
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@ -8,13 +8,13 @@ FLAGS_allocator_strategy=naive_best_fit \
FLAGS_fraction_of_gpu_memory_to_use=0.01 \
python3 ${BIN_DIR}/../../synthesize_e2e.py \
--am=fastspeech2_csmsc \
--am_config=${config_path} \
--am_ckpt=${train_output_path}/checkpoints/${ckpt_name} \
--am_stat=dump/train/speech_stats.npy \
--am_config=fastspeech2_nosil_baker_ckpt_0.4/default.yaml \
--am_ckpt=fastspeech2_nosil_baker_ckpt_0.4/snapshot_iter_76000.pdz \
--am_stat=fastspeech2_nosil_baker_ckpt_0.4/speech_stats.npy \
--voc=hifigan_csmsc \
--voc_config=hifigan_csmsc_ckpt_0.1.1/default.yaml \
--voc_ckpt=hifigan_csmsc_ckpt_0.1.1/snapshot_iter_2500000.pdz \
--voc_stat=hifigan_csmsc_ckpt_0.1.1/feats_stats.npy \
--voc_config=${config_path} \
--voc_ckpt=${train_output_path}/checkpoints/${ckpt_name} \
--voc_stat=dump/train/feats_stats.npy \
--lang=zh \
--text=${BIN_DIR}/../../assets/sentences.txt \
--output_dir=${train_output_path}/test_e2e \

6
examples/opencpop/svs1/README.md
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@ -118,6 +118,8 @@ pwgan_opencpop_ckpt_1.4.0.zip
```bash
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name}
```
use `pwgan` model as vocoder.
```text
usage: synthesize.py [-h]
[--am {diffsinger_opencpop}]
@ -170,8 +172,10 @@ optional arguments:
`local/pinyin_to_phone.txt` comes from the readme of the opencpop dataset, indicating the mapping from pinyin to phonemes in opencpop.
```bash
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name}
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name}
```
`--stage` controls the vocoder model during synthesis, which can be `0` or `1`, use `pwgan` or `hifigan` model as vocoder.
```text
usage: synthesize_e2e.py [-h]
[--am {speedyspeech_csmsc,speedyspeech_aishell3,fastspeech2_csmsc,fastspeech2_ljspeech,fastspeech2_aishell3,fastspeech2_vctk,tacotron2_csmsc,tacotron2_ljspeech}]

6
examples/opencpop/svs1/README_cn.md
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@ -121,6 +121,8 @@ pwgan_opencpop_ckpt_1.4.0.zip
```bash
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name}
```
使用 `pwgan` 模型作为声码器。
```text
usage: synthesize.py [-h]
[--am {diffsinger_opencpop}]
@ -173,8 +175,10 @@ optional arguments:
`local/pinyin_to_phone.txt`来源于opencpop数据集中的README，表示opencpop中拼音到音素的映射。
```bash
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name}
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name}
```
`--stage` 用于选择合成时使用的声码器模型，取值为 `0` 或 `1`，分别对应使用 `pwgan` 或 `hifigan` 模型作为声码器。
```text
usage: synthesize_e2e.py [-h]
[--am {speedyspeech_csmsc,speedyspeech_aishell3,fastspeech2_csmsc,fastspeech2_ljspeech,fastspeech2_aishell3,fastspeech2_vctk,tacotron2_csmsc,tacotron2_ljspeech}]

4
examples/opencpop/svs1/run.sh
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@ -32,6 +32,6 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
fi
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
# synthesize_e2e, vocoder is pwgan by default
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1
# synthesize_e2e, vocoder is pwgan by default, stage 1 will use hifigan as vocoder
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} || exit -1
fi

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