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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)
# create synthesizer
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!")
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