| | 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!") |
| |
|
