mirror of https://github.com/coqui-ai/TTS.git
Implement TTSTokenizer
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from typing import Callable, Dict, List, Union
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from TTS.tts.utils.text import cleaners
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from TTS.tts.utils.text.phonemizers import DEF_LANG_TO_PHONEMIZER, get_phonemizer_by_name
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from TTS.tts.utils.text.symbols import Graphemes, IPAPhonemes
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class TTSTokenizer:
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"""🐸TTS tokenizer to convert input characters to token IDs and back.
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Args:
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use_phonemes (bool):
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Whether to use phonemes instead of characters. Defaults to False.
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characters (Characters):
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A Characters object to use for character-to-ID and ID-to-character mappings.
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text_cleaner (callable):
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A function to pre-process the text before tokenization and phonemization. Defaults to None.
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phonemizer (Phonemizer):
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A phonemizer object or a dict that maps language codes to phonemizer objects. Defaults to None.
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"""
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def __init__(
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self,
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use_phonemes=False,
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text_cleaner: Callable = None,
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characters: "BaseCharacters" = None,
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phonemizer: Union["Phonemizer", Dict] = None,
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add_blank: bool = False,
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use_eos_bos=False,
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):
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self.text_cleaner = text_cleaner or (lambda x: x)
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self.use_phonemes = use_phonemes
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self.add_blank = add_blank
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self.use_eos_bos = use_eos_bos
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self.characters = characters
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self.phonemizer = phonemizer
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def encode(self, text: str) -> List[int]:
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"""Encodes a string of text as a sequence of IDs."""
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token_ids = []
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for char in text:
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idx = self.characters.char_to_id(char)
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token_ids.append(idx)
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return token_ids
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def decode(self, token_ids: List[int]) -> str:
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"""Decodes a sequence of IDs to a string of text."""
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text = ""
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for token_id in token_ids:
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text += self.characters.id_to_char(token_id)
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return text
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def text_to_ids(self, text: str, language: str = None) -> List[int]:
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"""Converts a string of text to a sequence of token IDs.
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Args:
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text(str):
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The text to convert to token IDs.
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language(str):
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The language code of the text. Defaults to None.
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1. Text normalizatin
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2. Phonemization (if use_phonemes is True)
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3. Add blank char between characters
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4. Add BOS and EOS characters
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5. Text to token IDs
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"""
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# TODO: text cleaner should pick the right routine based on the language
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text = self.text_cleaner(text)
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if self.use_phonemes:
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text = self.phonemizer.phonemize(text, separator="")
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if self.add_blank:
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text = self.intersperse_blank_char(text, True)
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if self.use_eos_bos:
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text = self.pad_with_bos_eos(text)
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return self.encode(text)
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def ids_to_text(self, id_sequence: List[int]) -> str:
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"""Converts a sequence of token IDs to a string of text."""
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return self.decode(id_sequence)
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def pad_with_bos_eos(self, char_sequence: List[str]):
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"""Pads a sequence with the special BOS and EOS characters."""
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return [self.characters.bos] + list(char_sequence) + [self.characters.eos]
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def intersperse_blank_char(self, char_sequence: List[str], use_blank_char: bool = False):
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char_to_use = self.characters.blank_char if use_blank_char else self.characters.pad
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result = [char_to_use] * (len(char_sequence) * 2 + 1)
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result[1::2] = char_sequence
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return result
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def print_logs(self, level: int = 1):
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indent = "\t" * level
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print(f"{indent}| > add_blank: {self.use_phonemes}")
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print(f"{indent}| > use_eos_bos: {self.use_phonemes}")
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print(f"{indent}| > use_phonemes: {self.use_phonemes}")
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print(f"{indent}| > phonemizer: {self.phonemizer.print_logs(level + 1)}")
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@staticmethod
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def init_from_config(config: "Coqpit"):
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"""Init Tokenizer object from the config.
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Args:
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config (Coqpit): Coqpit model config.
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"""
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if isinstance(config.text_cleaner, (str, list)):
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text_cleaner = getattr(cleaners, config.text_cleaner)
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if config.use_phonemes:
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characters = IPAPhonemes().init_from_config(config)
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phonemizer_kwargs = {"language": config.phoneme_language}
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phonemizer = get_phonemizer_by_name(DEF_LANG_TO_PHONEMIZER[config.phoneme_language], **phonemizer_kwargs)
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else:
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characters = Graphemes().init_from_config(config)
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return TTSTokenizer(config.use_phonemes, text_cleaner, characters, phonemizer, config.add_blank, config.enable_eos_bos_chars)
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