mirror of https://github.com/coqui-ai/TTS.git
Remove OLD TOKENIZATION ROUTINES
Eren Gölge
parent
53f696615b
commit
2480bbe937
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@ -1,276 +1 @@
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# -*- coding: utf-8 -*-
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# adapted from https://github.com/keithito/tacotron
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import re
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from typing import Dict, List
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import gruut
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from gruut_ipa import IPA
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from TTS.tts.utils.text import cleaners
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from TTS.tts.utils.text.chinese_mandarin.phonemizer import chinese_text_to_phonemes
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from TTS.tts.utils.text.japanese.phonemizer import japanese_text_to_phonemes
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from TTS.tts.utils.text.symbols import _bos, _eos, _punctuations, make_symbols, phonemes, symbols
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# pylint: disable=unnecessary-comprehension
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# Mappings from symbol to numeric ID and vice versa:
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_symbol_to_id = {s: i for i, s in enumerate(symbols)}
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_id_to_symbol = {i: s for i, s in enumerate(symbols)}
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_phonemes_to_id = {s: i for i, s in enumerate(phonemes)}
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_id_to_phonemes = {i: s for i, s in enumerate(phonemes)}
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_symbols = symbols
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_phonemes = phonemes
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# Regular expression matching text enclosed in curly braces:
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_CURLY_RE = re.compile(r"(.*?)\{(.+?)\}(.*)")
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# Regular expression matching punctuations, ignoring empty space
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PHONEME_PUNCTUATION_PATTERN = r"[" + _punctuations.replace(" ", "") + "]+"
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# Table for str.translate to fix gruut/TTS phoneme mismatch
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GRUUT_TRANS_TABLE = str.maketrans("g", "ɡ")
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def text2phone(text, language, use_espeak_phonemes=False, keep_stress=False):
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"""Convert graphemes to phonemes.
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Parameters:
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text (str): text to phonemize
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language (str): language of the text
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Returns:
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ph (str): phonemes as a string seperated by "|"
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ph = "ɪ|g|ˈ|z|æ|m|p|ə|l"
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"""
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# TO REVIEW : How to have a good implementation for this?
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if language == "zh-CN":
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ph = chinese_text_to_phonemes(text)
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return ph
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if language == "ja-jp":
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ph = japanese_text_to_phonemes(text)
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return ph
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if not gruut.is_language_supported(language):
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raise ValueError(f" [!] Language {language} is not supported for phonemization.")
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# Use gruut for phonemization
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ph_list = []
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for sentence in gruut.sentences(text, lang=language, espeak=use_espeak_phonemes):
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for word in sentence:
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if word.is_break:
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# Use actual character for break phoneme (e.g., comma)
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if ph_list:
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# Join with previous word
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ph_list[-1].append(word.text)
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else:
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# First word is punctuation
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ph_list.append([word.text])
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elif word.phonemes:
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# Add phonemes for word
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word_phonemes = []
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for word_phoneme in word.phonemes:
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if not keep_stress:
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# Remove primary/secondary stress
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word_phoneme = IPA.without_stress(word_phoneme)
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word_phoneme = word_phoneme.translate(GRUUT_TRANS_TABLE)
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if word_phoneme:
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# Flatten phonemes
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word_phonemes.extend(word_phoneme)
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if word_phonemes:
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ph_list.append(word_phonemes)
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# Join and re-split to break apart dipthongs, suprasegmentals, etc.
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ph_words = ["|".join(word_phonemes) for word_phonemes in ph_list]
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ph = "| ".join(ph_words)
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return ph
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def intersperse(sequence, token):
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result = [token] * (len(sequence) * 2 + 1)
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result[1::2] = sequence
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return result
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def pad_with_eos_bos(phoneme_sequence, tp=None):
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# pylint: disable=global-statement
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global _phonemes_to_id, _bos, _eos
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if tp:
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_bos = tp["bos"]
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_eos = tp["eos"]
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_, _phonemes = make_symbols(**tp)
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_phonemes_to_id = {s: i for i, s in enumerate(_phonemes)}
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return [_phonemes_to_id[_bos]] + list(phoneme_sequence) + [_phonemes_to_id[_eos]]
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def phoneme_to_sequence(
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text: str,
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cleaner_names: List[str],
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language: str,
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enable_eos_bos: bool = False,
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custom_symbols: List[str] = None,
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tp: Dict = None,
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add_blank: bool = False,
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use_espeak_phonemes: bool = False,
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) -> List[int]:
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"""Converts a string of phonemes to a sequence of IDs.
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If `custom_symbols` is provided, it will override the default symbols.
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Args:
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text (str): string to convert to a sequence
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cleaner_names (List[str]): names of the cleaner functions to run the text through
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language (str): text language key for phonemization.
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enable_eos_bos (bool): whether to append the end-of-sentence and beginning-of-sentence tokens.
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tp (Dict): dictionary of character parameters to use a custom character set.
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add_blank (bool): option to add a blank token between each token.
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use_espeak_phonemes (bool): use espeak based lexicons to convert phonemes to sequenc
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Returns:
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List[int]: List of integers corresponding to the symbols in the text
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"""
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# pylint: disable=global-statement
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global _phonemes_to_id, _phonemes
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if custom_symbols is not None:
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_phonemes = custom_symbols
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elif tp:
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_, _phonemes = make_symbols(**tp)
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_phonemes_to_id = {s: i for i, s in enumerate(_phonemes)}
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sequence = []
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clean_text = _clean_text(text, cleaner_names)
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to_phonemes = text2phone(clean_text, language, use_espeak_phonemes=use_espeak_phonemes)
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if to_phonemes is None:
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print("!! After phoneme conversion the result is None. -- {} ".format(clean_text))
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# iterate by skipping empty strings - NOTE: might be useful to keep it to have a better intonation.
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for phoneme in filter(None, to_phonemes.split("|")):
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sequence += _phoneme_to_sequence(phoneme)
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# Append EOS char
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if enable_eos_bos:
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sequence = pad_with_eos_bos(sequence, tp=tp)
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if add_blank:
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sequence = intersperse(sequence, len(_phonemes)) # add a blank token (new), whose id number is len(_phonemes)
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return sequence
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def sequence_to_phoneme(sequence: List, tp: Dict = None, add_blank=False, custom_symbols: List["str"] = None):
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# pylint: disable=global-statement
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"""Converts a sequence of IDs back to a string"""
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global _id_to_phonemes, _phonemes
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if add_blank:
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sequence = list(filter(lambda x: x != len(_phonemes), sequence))
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result = ""
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if custom_symbols is not None:
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_phonemes = custom_symbols
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elif tp:
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_, _phonemes = make_symbols(**tp)
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_id_to_phonemes = {i: s for i, s in enumerate(_phonemes)}
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for symbol_id in sequence:
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if symbol_id in _id_to_phonemes:
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s = _id_to_phonemes[symbol_id]
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result += s
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return result.replace("}{", " ")
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def text_to_sequence(
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text: str, cleaner_names: List[str], custom_symbols: List[str] = None, tp: Dict = None, add_blank: bool = False
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) -> List[int]:
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"""Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
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If `custom_symbols` is provided, it will override the default symbols.
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Args:
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text (str): string to convert to a sequence
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cleaner_names (List[str]): names of the cleaner functions to run the text through
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tp (Dict): dictionary of character parameters to use a custom character set.
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add_blank (bool): option to add a blank token between each token.
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Returns:
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List[int]: List of integers corresponding to the symbols in the text
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"""
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# pylint: disable=global-statement
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global _symbol_to_id, _symbols
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if custom_symbols is not None:
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_symbols = custom_symbols
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elif tp:
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_symbols, _ = make_symbols(**tp)
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_symbol_to_id = {s: i for i, s in enumerate(_symbols)}
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sequence = []
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# Check for curly braces and treat their contents as ARPAbet:
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while text:
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m = _CURLY_RE.match(text)
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if not m:
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sequence += _symbols_to_sequence(_clean_text(text, cleaner_names))
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break
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sequence += _symbols_to_sequence(_clean_text(m.group(1), cleaner_names))
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sequence += _arpabet_to_sequence(m.group(2))
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text = m.group(3)
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if add_blank:
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sequence = intersperse(sequence, len(_symbols)) # add a blank token (new), whose id number is len(_symbols)
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return sequence
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def sequence_to_text(sequence: List, tp: Dict = None, add_blank=False, custom_symbols: List[str] = None):
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"""Converts a sequence of IDs back to a string"""
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# pylint: disable=global-statement
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global _id_to_symbol, _symbols
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if add_blank:
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sequence = list(filter(lambda x: x != len(_symbols), sequence))
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if custom_symbols is not None:
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_symbols = custom_symbols
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_id_to_symbol = {i: s for i, s in enumerate(_symbols)}
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elif tp:
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_symbols, _ = make_symbols(**tp)
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_id_to_symbol = {i: s for i, s in enumerate(_symbols)}
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result = ""
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for symbol_id in sequence:
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if symbol_id in _id_to_symbol:
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s = _id_to_symbol[symbol_id]
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# Enclose ARPAbet back in curly braces:
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if len(s) > 1 and s[0] == "@":
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s = "{%s}" % s[1:]
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result += s
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return result.replace("}{", " ")
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def _clean_text(text, cleaner_names):
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for name in cleaner_names:
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cleaner = getattr(cleaners, name)
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if not cleaner:
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raise Exception("Unknown cleaner: %s" % name)
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text = cleaner(text)
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return text
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def _symbols_to_sequence(syms):
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return [_symbol_to_id[s] for s in syms if _should_keep_symbol(s)]
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def _phoneme_to_sequence(phons):
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return [_phonemes_to_id[s] for s in list(phons) if _should_keep_phoneme(s)]
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def _arpabet_to_sequence(text):
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return _symbols_to_sequence(["@" + s for s in text.split()])
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def _should_keep_symbol(s):
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return s in _symbol_to_id and s not in ["~", "^", "_"]
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def _should_keep_phoneme(p):
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return p in _phonemes_to_id and p not in ["~", "^", "_"]
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from TTS.tts.utils.text.tokenizer import TTSTokenizer
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