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Issue看板
“500f283dd6923fc1abfd240ad838d6b629c0b8f2”上不存在“paddlespeech/s2t/training/optimizer/adadelta.py”
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25530223
编写于
2月 16, 2023
作者:
H
HuangLiangJie
提交者:
GitHub
2月 16, 2023
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[TTS]Cantonese TTS checkpoint for e2e, test=tts (#2932)
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-2
examples/canton/tts3/README.md
examples/canton/tts3/README.md
+38
-0
examples/canton/tts3/run.sh
examples/canton/tts3/run.sh
+2
-2
未找到文件。
examples/canton/tts3/README.md
浏览文件 @
25530223
...
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@@ -75,3 +75,41 @@ Also, there is a `metadata.jsonl` in each subfolder. It is a table-like file tha
### Training details can refer to the script of [examples/aishell3/tts3](../../aishell3/tts3).
## Pretrained Model
Pretrained FastSpeech2 model with no silence in the edge of audios:
-
[
fastspeech2_canton_ckpt_1.4.0.zip
](
https://paddlespeech.bj.bcebos.com/Parakeet/released_models/fastspeech2/fastspeech2_canton_ckpt_1.4.0.zip
)
FastSpeech2 checkpoint contains files listed below.
```
text
fastspeech2_canton_ckpt_1.4.0
├── default.yaml # default config used to train fastspeech2
├── energy_stats.npy # statistics used to normalize energy when training fastspeech2
├── phone_id_map.txt # phone vocabulary file when training fastspeech2
├── pitch_stats.npy # statistics used to normalize pitch when training fastspeech2
├── snapshot_iter_140000.pdz # model parameters and optimizer states
├── speaker_id_map.txt # speaker id map file when training a multi-speaker fastspeech2
└── speech_stats.npy # statistics used to normalize spectrogram when training fastspeech2
```
You can use the following scripts to synthesize for
`${BIN_DIR}/../sentences_canton.txt`
using pretrained fastspeech2 and parallel wavegan models.
```
bash
source
path.sh
FLAGS_allocator_strategy
=
naive_best_fit
\
FLAGS_fraction_of_gpu_memory_to_use
=
0.01
\
python3
${
BIN_DIR
}
/../synthesize_e2e.py
\
--am
=
fastspeech2_aishell3
\
--am_config
=
fastspeech2_canton_ckpt_1.4.0/default.yaml
\
--am_ckpt
=
fastspeech2_canton_ckpt_1.4.0/snapshot_iter_140000.pdz
\
--am_stat
=
fastspeech2_canton_ckpt_1.4.0/speech_stats.npy
\
--voc
=
pwgan_aishell3
\
--voc_config
=
pwg_aishell3_ckpt_0.5/default.yaml
\
--voc_ckpt
=
pwg_aishell3_ckpt_0.5/snapshot_iter_1000000.pdz
\
--voc_stat
=
pwg_aishell3_ckpt_0.5/feats_stats.npy
\
--lang
=
canton
\
--text
=
${
BIN_DIR
}
/../sentences_canton.txt
\
--output_dir
=
exp/default/test_e2e
\
--phones_dict
=
fastspeech2_canton_ckpt_1.4.0/phone_id_map.txt
\
--speaker_dict
=
fastspeech2_canton_ckpt_1.4.0/speaker_id_map.txt
\
--spk_id
=
0
\
--inference_dir
=
exp/default/inference
```
examples/canton/tts3/run.sh
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...
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@@ -3,14 +3,14 @@
set
-e
source
path.sh
gpus
=
0
gpus
=
0
,1
stage
=
0
stop_stage
=
100
conf_path
=
conf/default.yaml
train_output_path
=
exp/default
ckpt_name
=
snapshot_iter_
28
0000.pdz
ckpt_name
=
snapshot_iter_
14
0000.pdz
# with the following command, you can choose the stage range you want to run
# such as `./run.sh --stage 0 --stop-stage 0`
...
...
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