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