coqui-tts/TTS/api.py

147 lines
6.4 KiB
Python

from pathlib import Path
from TTS.utils.manage import ModelManager
from TTS.utils.synthesizer import Synthesizer
class TTS:
"""TODO: Add voice conversion and Capacitron support."""
def __init__(self, model_name: str = None, progress_bar: bool = True, gpu=False):
"""🐸TTS python interface that allows to load and use the released models.
Example with a multi-speaker model:
>>> from TTS.api import TTS
>>> tts = TTS(TTS.list_models()[0])
>>> wav = tts.tts("This is a test! This is also a test!!", speaker=tts.speakers[0], language=tts.languages[0])
>>> tts.tts_to_file(text="Hello world!", speaker=tts.speakers[0], language=tts.languages[0], file_path="output.wav")
Example with a single-speaker model:
>>> tts = TTS(model_name="tts_models/de/thorsten/tacotron2-DDC", progress_bar=False, gpu=False)
>>> tts.tts_to_file(text="Ich bin eine Testnachricht.", file_path="output.wav")
Args:
model_name (str, optional): Model name to load. You can list models by ```tts.models```. Defaults to None.
progress_bar (bool, optional): Whether to pring a progress bar while downloading a model. Defaults to True.
gpu (bool, optional): Enable/disable GPU. Some models might be too slow on CPU. Defaults to False.
"""
self.manager = ModelManager(models_file=self.get_models_file_path(), progress_bar=progress_bar, verbose=False)
self.synthesizer = None
if model_name:
self.load_model_by_name(model_name, gpu)
@property
def models(self):
return self.manager.list_tts_models()
@property
def is_multi_speaker(self):
if hasattr(self.synthesizer.tts_model, "speaker_manager") and self.synthesizer.tts_model.speaker_manager:
return self.synthesizer.tts_model.speaker_manager.num_speakers > 1
return False
@property
def is_multi_lingual(self):
if hasattr(self.synthesizer.tts_model, "language_manager") and self.synthesizer.tts_model.language_manager:
return self.synthesizer.tts_model.language_manager.num_languages > 1
return False
@property
def speakers(self):
if not self.is_multi_speaker:
return None
return self.synthesizer.tts_model.speaker_manager.speaker_names
@property
def languages(self):
if not self.is_multi_lingual:
return None
return self.synthesizer.tts_model.language_manager.language_names
@staticmethod
def get_models_file_path():
return Path(__file__).parent / ".models.json"
@staticmethod
def list_models():
manager = ModelManager(models_file=TTS.get_models_file_path(), progress_bar=False, verbose=False)
return manager.list_tts_models()
def download_model_by_name(self, model_name: str):
model_path, config_path, model_item = self.manager.download_model(model_name)
if model_item["default_vocoder"] is None:
return model_path, config_path, None, None
vocoder_path, vocoder_config_path, _ = self.manager.download_model(model_item["default_vocoder"])
return model_path, config_path, vocoder_path, vocoder_config_path
def load_model_by_name(self, model_name: str, gpu: bool = False):
model_path, config_path, vocoder_path, vocoder_config_path = self.download_model_by_name(model_name)
# init synthesizer
# None values are fetch from the model
self.synthesizer = Synthesizer(
tts_checkpoint=model_path,
tts_config_path=config_path,
tts_speakers_file=None,
tts_languages_file=None,
vocoder_checkpoint=vocoder_path,
vocoder_config=vocoder_config_path,
encoder_checkpoint=None,
encoder_config=None,
use_cuda=gpu,
)
def _check_arguments(self, speaker: str = None, language: str = None):
if self.is_multi_speaker and speaker is None:
raise ValueError("Model is multi-speaker but no speaker is provided.")
if self.is_multi_lingual and language is None:
raise ValueError("Model is multi-lingual but no language is provided.")
if not self.is_multi_speaker and speaker is not None:
raise ValueError("Model is not multi-speaker but speaker is provided.")
if not self.is_multi_lingual and language is not None:
raise ValueError("Model is not multi-lingual but language is provided.")
def tts(self, text: str, speaker: str = None, language: str = None):
"""Convert text to speech.
Args:
text (str):
Input text to synthesize.
speaker (str, optional):
Speaker name for multi-speaker. You can check whether loaded model is multi-speaker by
`tts.is_multi_speaker` and list speakers by `tts.speakers`. Defaults to None.
language (str, optional):
Language code for multi-lingual models. You can check whether loaded model is multi-lingual
`tts.is_multi_lingual` and list available languages by `tts.languages`. Defaults to None.
"""
self._check_arguments(speaker=speaker, language=language)
wav = self.synthesizer.tts(
text=text,
speaker_name=speaker,
language_name=language,
speaker_wav=None,
reference_wav=None,
style_wav=None,
style_text=None,
reference_speaker_name=None,
)
return wav
def tts_to_file(self, text: str, speaker: str = None, language: str = None, file_path: str = "output.wav"):
"""Convert text to speech.
Args:
text (str):
Input text to synthesize.
speaker (str, optional):
Speaker name for multi-speaker. You can check whether loaded model is multi-speaker by
`tts.is_multi_speaker` and list speakers by `tts.speakers`. Defaults to None.
language (str, optional):
Language code for multi-lingual models. You can check whether loaded model is multi-lingual
`tts.is_multi_lingual` and list available languages by `tts.languages`. Defaults to None.
file_path (str, optional):
Output file path. Defaults to "output.wav".
"""
wav = self.tts(text=text, speaker=speaker, language=language)
self.synthesizer.save_wav(wav=wav, path=file_path)