| 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!") |
|
|
