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Merge pull request #1443 from yt605155624/add_new_ttscli

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[CLI]update tts cli
pull/1447/head
TianYuan 3 years ago committed by GitHub
parent d6edb62d3e 2cec8f6c76
commit ad79d15e32
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GPG Key ID: 4AEE18F83AFDEB23
5 changed files with 96 additions and 19 deletions
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5
paddlespeech/cli/cls/infer.py
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@ -114,8 +114,9 @@ class CLSExecutor(BaseExecutor):
"""
Download and returns pretrained resources path of current task.
"""
assert tag in pretrained_models, 'Can not find pretrained resources of {}.'.format(
tag)
support_models = list(pretrained_models.keys())
assert tag in pretrained_models, 'The model "{}" you want to use has not been supported, please choose other models.\nThe support models includes:\n\t\t{}\n'.format(
tag, '\n\t\t'.join(support_models))
res_path = os.path.join(MODEL_HOME, tag)
decompressed_path = download_and_decompress(pretrained_models[tag],

5
paddlespeech/cli/st/infer.py
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@ -112,8 +112,9 @@ class STExecutor(BaseExecutor):
"""
Download and returns pretrained resources path of current task.
"""
assert tag in pretrained_models, "Can not find pretrained resources of {}.".format(
tag)
support_models = list(pretrained_models.keys())
assert tag in pretrained_models, 'The model "{}" you want to use has not been supported, please choose other models.\nThe support models includes:\n\t\t{}\n'.format(
tag, '\n\t\t'.join(support_models))
res_path = os.path.join(MODEL_HOME, tag)
decompressed_path = download_and_decompress(pretrained_models[tag],

5
paddlespeech/cli/text/infer.py
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@ -124,8 +124,9 @@ class TextExecutor(BaseExecutor):
"""
Download and returns pretrained resources path of current task.
"""
assert tag in pretrained_models, 'Can not find pretrained resources of {}.'.format(
tag)
support_models = list(pretrained_models.keys())
assert tag in pretrained_models, 'The model "{}" you want to use has not been supported, please choose other models.\nThe support models includes:\n\t\t{}\n'.format(
tag, '\n\t\t'.join(support_models))
res_path = os.path.join(MODEL_HOME, tag)
decompressed_path = download_and_decompress(pretrained_models[tag],

92
paddlespeech/cli/tts/infer.py
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@ -117,6 +117,36 @@ pretrained_models = {
'speaker_dict':
'speaker_id_map.txt',
},
# tacotron2
"tacotron2_csmsc-zh": {
'url':
'https://paddlespeech.bj.bcebos.com/Parakeet/released_models/tacotron2/tacotron2_csmsc_ckpt_0.2.0.zip',
'md5':
'0df4b6f0bcbe0d73c5ed6df8867ab91a',
'config':
'default.yaml',
'ckpt':
'snapshot_iter_30600.pdz',
'speech_stats':
'speech_stats.npy',
'phones_dict':
'phone_id_map.txt',
},
"tacotron2_ljspeech-en": {
'url':
'https://paddlespeech.bj.bcebos.com/Parakeet/released_models/tacotron2/tacotron2_ljspeech_ckpt_0.2.0.zip',
'md5':
'6a5eddd81ae0e81d16959b97481135f3',
'config':
'default.yaml',
'ckpt':
'snapshot_iter_60300.pdz',
'speech_stats':
'speech_stats.npy',
'phones_dict':
'phone_id_map.txt',
},
# pwgan
"pwgan_csmsc-zh": {
'url':
@ -205,6 +235,20 @@ pretrained_models = {
'speech_stats':
'feats_stats.npy',
},
# wavernn
"wavernn_csmsc-zh": {
'url':
'https://paddlespeech.bj.bcebos.com/Parakeet/released_models/wavernn/wavernn_csmsc_ckpt_0.2.0.zip',
'md5':
'ee37b752f09bcba8f2af3b777ca38e13',
'config':
'default.yaml',
'ckpt':
'snapshot_iter_400000.pdz',
'speech_stats':
'feats_stats.npy',
}
}
model_alias = {
@ -217,6 +261,10 @@ model_alias = {
"paddlespeech.t2s.models.fastspeech2:FastSpeech2",
"fastspeech2_inference":
"paddlespeech.t2s.models.fastspeech2:FastSpeech2Inference",
"tacotron2":
"paddlespeech.t2s.models.tacotron2:Tacotron2",
"tacotron2_inference":
"paddlespeech.t2s.models.tacotron2:Tacotron2Inference",
# voc
"pwgan":
"paddlespeech.t2s.models.parallel_wavegan:PWGGenerator",
@ -234,6 +282,10 @@ model_alias = {
"paddlespeech.t2s.models.hifigan:HiFiGANGenerator",
"hifigan_inference":
"paddlespeech.t2s.models.hifigan:HiFiGANInference",
"wavernn":
"paddlespeech.t2s.models.wavernn:WaveRNN",
"wavernn_inference":
"paddlespeech.t2s.models.wavernn:WaveRNNInference",
}
@ -253,9 +305,13 @@ class TTSExecutor(BaseExecutor):
type=str,
default='fastspeech2_csmsc',
choices=[
'speedyspeech_csmsc', 'fastspeech2_csmsc',
'fastspeech2_ljspeech', 'fastspeech2_aishell3',
'fastspeech2_vctk'
'speedyspeech_csmsc',
'fastspeech2_csmsc',
'fastspeech2_ljspeech',
'fastspeech2_aishell3',
'fastspeech2_vctk',
'tacotron2_csmsc',
'tacotron2_ljspeech',
],
help='Choose acoustic model type of tts task.')
self.parser.add_argument(
@ -300,8 +356,14 @@ class TTSExecutor(BaseExecutor):
type=str,
default='pwgan_csmsc',
choices=[
'pwgan_csmsc', 'pwgan_ljspeech', 'pwgan_aishell3', 'pwgan_vctk',
'mb_melgan_csmsc', 'style_melgan_csmsc', 'hifigan_csmsc'
'pwgan_csmsc',
'pwgan_ljspeech',
'pwgan_aishell3',
'pwgan_vctk',
'mb_melgan_csmsc',
'style_melgan_csmsc',
'hifigan_csmsc',
'wavernn_csmsc',
],
help='Choose vocoder type of tts task.')
@ -340,8 +402,9 @@ class TTSExecutor(BaseExecutor):
"""
Download and returns pretrained resources path of current task.
"""
assert tag in pretrained_models, 'Can not find pretrained resources of {}.'.format(
tag)
support_models = list(pretrained_models.keys())
assert tag in pretrained_models, 'The model "{}" you want to use has not been supported, please choose other models.\nThe support models includes:\n\t\t{}\n'.format(
tag, '\n\t\t'.join(support_models))
res_path = os.path.join(MODEL_HOME, tag)
decompressed_path = download_and_decompress(pretrained_models[tag],
@ -488,6 +551,8 @@ class TTSExecutor(BaseExecutor):
vocab_size=vocab_size,
tone_size=tone_size,
**self.am_config["model"])
elif am_name == 'tacotron2':
am = am_class(idim=vocab_size, odim=odim, **self.am_config["model"])
am.set_state_dict(paddle.load(self.am_ckpt)["main_params"])
am.eval()
@ -505,10 +570,15 @@ class TTSExecutor(BaseExecutor):
voc_class = dynamic_import(voc_name, model_alias)
voc_inference_class = dynamic_import(voc_name + '_inference',
model_alias)
voc = voc_class(**self.voc_config["generator_params"])
voc.set_state_dict(paddle.load(self.voc_ckpt)["generator_params"])
voc.remove_weight_norm()
voc.eval()
if voc_name != 'wavernn':
voc = voc_class(**self.voc_config["generator_params"])
voc.set_state_dict(paddle.load(self.voc_ckpt)["generator_params"])
voc.remove_weight_norm()
voc.eval()
else:
voc = voc_class(**self.voc_config["model"])
voc.set_state_dict(paddle.load(self.voc_ckpt)["main_params"])
voc.eval()
voc_mu, voc_std = np.load(self.voc_stat)
voc_mu = paddle.to_tensor(voc_mu)
voc_std = paddle.to_tensor(voc_std)

8
tests/unit/cli/test_cli.sh
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@ -19,8 +19,12 @@ paddlespeech tts --voc mb_melgan_csmsc --input "你好，欢迎使用百度飞
paddlespeech tts --voc style_melgan_csmsc --input "你好，欢迎使用百度飞桨深度学习框架！"
paddlespeech tts --voc hifigan_csmsc --input "你好，欢迎使用百度飞桨深度学习框架！"
paddlespeech tts --am fastspeech2_aishell3 --voc pwgan_aishell3 --input "你好，欢迎使用百度飞桨深度学习框架！" --spk_id 0
paddlespeech tts --am fastspeech2_ljspeech --voc pwgan_ljspeech --lang en --input "hello world"
paddlespeech tts --am fastspeech2_vctk --voc pwgan_vctk --input "hello, boys" --lang en --spk_id 0
paddlespeech tts --am fastspeech2_ljspeech --voc pwgan_ljspeech --lang en --input "Life was like a box of chocolates, you never know what you're gonna get."
paddlespeech tts --am fastspeech2_vctk --voc pwgan_vctk --input "Life was like a box of chocolates, you never know what you're gonna get." --lang en --spk_id 0
paddlespeech tts --am tacotron2_csmsc --input "你好，欢迎使用百度飞桨深度学习框架！"
paddlespeech tts --am tacotron2_csmsc --voc wavernn_csmsc --input "你好，欢迎使用百度飞桨深度学习框架！"
paddlespeech tts --am tacotron2_ljspeech --voc pwgan_ljspeech --lang en --input "Life was like a box of chocolates, you never know what you're gonna get."
# Speech Translation (only support linux)
paddlespeech st --input ./en.wav

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