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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!") | |