|
dependencies = [ |
|
'torch', 'gdown', 'pysbd', 'gruut', 'anyascii', 'pypinyin', 'coqpit', 'mecab-python3', 'unidic-lite' |
|
] |
|
import torch |
|
|
|
from TTS.utils.manage import ModelManager |
|
from TTS.utils.synthesizer import Synthesizer |
|
|
|
|
|
def tts(model_name='tts_models/en/ljspeech/tacotron2-DCA', |
|
vocoder_name=None, |
|
use_cuda=False): |
|
"""TTS entry point for PyTorch Hub that provides a Synthesizer object to synthesize speech from a give text. |
|
|
|
Example: |
|
>>> synthesizer = torch.hub.load('coqui-ai/TTS', 'tts', source='github') |
|
>>> wavs = synthesizer.tts("This is a test! This is also a test!!") |
|
wavs - is a list of values of the synthesized speech. |
|
|
|
Args: |
|
model_name (str, optional): One of the model names from .model.json. Defaults to 'tts_models/en/ljspeech/tacotron2-DCA'. |
|
vocoder_name (str, optional): One of the model names from .model.json. Defaults to 'vocoder_models/en/ljspeech/multiband-melgan'. |
|
pretrained (bool, optional): [description]. Defaults to True. |
|
|
|
Returns: |
|
TTS.utils.synthesizer.Synthesizer: Synthesizer object wrapping both vocoder and tts models. |
|
""" |
|
manager = ModelManager() |
|
|
|
model_path, config_path, model_item = manager.download_model(model_name) |
|
vocoder_name = model_item[ |
|
'default_vocoder'] if vocoder_name is None else vocoder_name |
|
vocoder_path, vocoder_config_path, _ = manager.download_model(vocoder_name) |
|
|
|
|
|
synt = Synthesizer(tts_checkpoint=model_path, |
|
tts_config_path=config_path, |
|
vocoder_checkpoint=vocoder_path, |
|
vocoder_config=vocoder_config_path, |
|
use_cuda=use_cuda) |
|
return synt |
|
|
|
|
|
if __name__ == '__main__': |
|
synthesizer = torch.hub.load('coqui-ai/TTS:dev', 'tts', source='github') |
|
synthesizer.tts("This is a test!") |
|
|
