Refactor: style_bert_vits2/text_processing/cleaner.py integrated into style_bert_vits2/text_processing/__init__.py
This was often used in 3 function sets and felt like a wasteful division with few lines.
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@@ -11,28 +11,6 @@ from style_bert_vits2.text_processing.symbols import (
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_symbol_to_id = {s: i for i, s in enumerate(SYMBOLS)}
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def cleaned_text_to_sequence(cleaned_text: str, tones: list[int], language: Languages) -> tuple[list[int], list[int], list[int]]:
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"""
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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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Args:
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cleaned_text (str): string to convert to a sequence
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tones (list[int]): List of tones
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language (Languages): Language of the text
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Returns:
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tuple[list[int], list[int], list[int]]: List of integers corresponding to the symbols in the text
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"""
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phones = [_symbol_to_id[symbol] for symbol in cleaned_text]
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tone_start = LANGUAGE_TONE_START_MAP[language]
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tones = [i + tone_start for i in tones]
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lang_id = LANGUAGE_ID_MAP[language]
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lang_ids = [lang_id for i in phones]
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return phones, tones, lang_ids
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def extract_bert_feature(
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text: str,
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word2ph: list[int],
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@@ -66,3 +44,64 @@ def extract_bert_feature(
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raise ValueError(f"Language {language} not supported")
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return extract_bert_feature(text, word2ph, device, assist_text, assist_text_weight)
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def clean_text(
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text: str,
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language: Languages,
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use_jp_extra: bool = True,
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raise_yomi_error: bool = False,
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) -> tuple[str, list[str], list[int], list[int]]:
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"""
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テキストをクリーニングし、音素に変換する
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Args:
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text (str): クリーニングするテキスト
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language (Languages): テキストの言語
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use_jp_extra (bool, optional): テキストが日本語の場合に JP-Extra モデルを利用するかどうか。Defaults to True.
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raise_yomi_error (bool, optional): False の場合、読めない文字が消えたような扱いとして処理される。Defaults to False.
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Returns:
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tuple[str, list[str], list[int], list[int]]: クリーニングされたテキストと、音素・アクセント・元のテキストの各文字に音素が何個割り当てられるかのリスト
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"""
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# Changed to import inside if condition to avoid unnecessary import
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if language == Languages.JP:
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from style_bert_vits2.text_processing.japanese.g2p import g2p
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from style_bert_vits2.text_processing.japanese.normalizer import normalize_text
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norm_text = normalize_text(text)
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phones, tones, word2ph = g2p(norm_text, use_jp_extra, raise_yomi_error)
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elif language == Languages.EN:
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from ...text import english as language_module
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norm_text = language_module.normalize_text(text)
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phones, tones, word2ph = language_module.g2p(norm_text)
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elif language == Languages.ZH:
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from ...text import chinese as language_module
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norm_text = language_module.normalize_text(text)
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phones, tones, word2ph = language_module.g2p(norm_text)
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else:
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raise ValueError(f"Language {language} not supported")
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return norm_text, phones, tones, word2ph
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def cleaned_text_to_sequence(cleaned_phones: list[str], tones: list[int], language: Languages) -> tuple[list[int], list[int], list[int]]:
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"""
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テキスト文字列を、テキスト内の記号に対応する一連の ID に変換する
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Args:
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cleaned_phones (list[str]): clean_text() でクリーニングされた音素のリスト (?)
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tones (list[int]): 各音素のアクセント
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language (Languages): テキストの言語
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Returns:
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tuple[list[int], list[int], list[int]]: List of integers corresponding to the symbols in the text
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"""
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phones = [_symbol_to_id[symbol] for symbol in cleaned_phones]
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tone_start = LANGUAGE_TONE_START_MAP[language]
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tones = [i + tone_start for i in tones]
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lang_id = LANGUAGE_ID_MAP[language]
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lang_ids = [lang_id for i in phones]
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return phones, tones, lang_ids
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@@ -1,40 +0,0 @@
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from style_bert_vits2.constants import Languages
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def clean_text(
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text: str,
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language: Languages,
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use_jp_extra: bool = True,
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raise_yomi_error: bool = False,
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) -> tuple[str, list[str], list[int], list[int]]:
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"""
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テキストをクリーニングし、音素に変換する
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Args:
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text (str): クリーニングするテキスト
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language (Languages): テキストの言語
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use_jp_extra (bool, optional): テキストが日本語の場合に JP-Extra モデルを利用するかどうか。Defaults to True.
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raise_yomi_error (bool, optional): False の場合、読めない文字が消えたような扱いとして処理される。Defaults to False.
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Returns:
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tuple[str, list[str], list[int], list[int]]: クリーニングされたテキストと、音素・アクセント・元のテキストの各文字に音素が何個割り当てられるかのリスト
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"""
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# Changed to import inside if condition to avoid unnecessary import
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if language == Languages.JP:
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from style_bert_vits2.text_processing.japanese.g2p import g2p
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from style_bert_vits2.text_processing.japanese.normalizer import normalize_text
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norm_text = normalize_text(text)
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phones, tones, word2ph = g2p(norm_text, use_jp_extra, raise_yomi_error)
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elif language == Languages.EN:
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from ...text import english as language_module
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norm_text = language_module.normalize_text(text)
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phones, tones, word2ph = language_module.g2p(norm_text)
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elif language == Languages.ZH:
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from ...text import chinese as language_module
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norm_text = language_module.normalize_text(text)
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phones, tones, word2ph = language_module.g2p(norm_text)
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else:
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raise ValueError(f"Language {language} not supported")
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return norm_text, phones, tones, word2ph
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