mirror of https://github.com/coqui-ai/TTS.git
Eren Gölge
GitHub
commit
73b4083c6c
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@ -1 +1 @@
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__version__ = "0.0.14.1"
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__version__ = "0.0.14"
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@ -424,3 +424,17 @@ def baker(root_path: str, meta_file: str) -> List[List[str]]:
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wav_path = os.path.join(root_path, "clips_22", wav_name)
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items.append([text, wav_path, speaker_name])
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return items
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def kokoro(root_path, meta_file):
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"""Japanese single-speaker dataset from https://github.com/kaiidams/Kokoro-Speech-Dataset"""
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txt_file = os.path.join(root_path, meta_file)
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items = []
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speaker_name = "kokoro"
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with open(txt_file, "r") as ttf:
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for line in ttf:
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cols = line.split("|")
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wav_file = os.path.join(root_path, "wavs", cols[0] + '.wav')
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text = cols[2].replace(" ", "")
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items.append([text, wav_file, speaker_name])
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return items
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@ -6,6 +6,7 @@ from packaging import version
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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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@ -39,6 +40,11 @@ def text2phone(text, language):
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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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raise ValueError(f" [!] Language {language} is not supported for phonemization.")
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@ -0,0 +1,379 @@
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# Convert Japanese text to phonemes which is
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# compatible with Julius https://github.com/julius-speech/segmentation-kit
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import re
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import MeCab
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_CONVRULES = [
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# Conversion of 2 letters
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'アァ/ a a',
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'イィ/ i i',
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'イェ/ i e',
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'イャ/ y a',
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'ウゥ/ u:',
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'エェ/ e e',
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'オォ/ o:',
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'カァ/ k a:',
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'キィ/ k i:',
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'クゥ/ k u:',
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'クャ/ ky a',
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'クュ/ ky u',
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'クョ/ ky o',
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'ケェ/ k e:',
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'コォ/ k o:',
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'ガァ/ g a:',
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'ギィ/ g i:',
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'グゥ/ g u:',
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'グャ/ gy a',
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'グュ/ gy u',
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'グョ/ gy o',
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'ゲェ/ g e:',
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'ゴォ/ g o:',
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'サァ/ s a:',
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'シィ/ sh i:',
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'スゥ/ s u:',
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'スャ/ sh a',
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'スュ/ sh u',
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'スョ/ sh o',
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'セェ/ s e:',
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'ソォ/ s o:',
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'ザァ/ z a:',
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'ジィ/ j i:',
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'ズゥ/ z u:',
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'ズャ/ zy a',
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'ズュ/ zy u',
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'ズョ/ zy o',
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'ゼェ/ z e:',
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'ゾォ/ z o:',
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'タァ/ t a:',
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'チィ/ ch i:',
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'ツァ/ ts a',
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'ツィ/ ts i',
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'ツゥ/ ts u:',
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'ツャ/ ch a',
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'ツュ/ ch u',
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'ツョ/ ch o',
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'ツェ/ ts e',
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'ツォ/ ts o',
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'テェ/ t e:',
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'トォ/ t o:',
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'ダァ/ d a:',
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'ヂィ/ j i:',
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'ヅゥ/ d u:',
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'ヅャ/ zy a',
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'ヅュ/ zy u',
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'ヅョ/ zy o',
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'デェ/ d e:',
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'ドォ/ d o:',
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'ナァ/ n a:',
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'ニィ/ n i:',
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'ヌゥ/ n u:',
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'ヌャ/ ny a',
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'ヌュ/ ny u',
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'ヌョ/ ny o',
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'ネェ/ n e:',
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'ノォ/ n o:',
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'ハァ/ h a:',
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'ヒィ/ h i:',
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'フゥ/ f u:',
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'フャ/ hy a',
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'フュ/ hy u',
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'フョ/ hy o',
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'ヘェ/ h e:',
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'ホォ/ h o:',
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'バァ/ b a:',
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'ビィ/ b i:',
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'ブゥ/ b u:',
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'フャ/ hy a',
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'ブュ/ by u',
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'フョ/ hy o',
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'ベェ/ b e:',
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'ボォ/ b o:',
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'パァ/ p a:',
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'ピィ/ p i:',
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'プゥ/ p u:',
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'プャ/ py a',
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'プュ/ py u',
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'プョ/ py o',
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'ペェ/ p e:',
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'ポォ/ p o:',
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'マァ/ m a:',
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'ミィ/ m i:',
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'ムゥ/ m u:',
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'ムャ/ my a',
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'ムュ/ my u',
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'ムョ/ my o',
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'メェ/ m e:',
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'モォ/ m o:',
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'ヤァ/ y a:',
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'ユゥ/ y u:',
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'ユャ/ y a:',
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'ユュ/ y u:',
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'ユョ/ y o:',
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'ヨォ/ y o:',
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'ラァ/ r a:',
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'リィ/ r i:',
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'ルゥ/ r u:',
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'ルャ/ ry a',
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'ルュ/ ry u',
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'ルョ/ ry o',
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'レェ/ r e:',
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'ロォ/ r o:',
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'ワァ/ w a:',
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'ヲォ/ o:',
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'ディ/ d i',
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'デェ/ d e:',
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'デャ/ dy a',
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'デュ/ dy u',
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'デョ/ dy o',
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'ティ/ t i',
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'テェ/ t e:',
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'テャ/ ty a',
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'テュ/ ty u',
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'テョ/ ty o',
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'スィ/ s i',
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'ズァ/ z u a',
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'ズィ/ z i',
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'ズゥ/ z u',
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'ズャ/ zy a',
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'ズュ/ zy u',
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'ズョ/ zy o',
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'ズェ/ z e',
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'ズォ/ z o',
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'キャ/ ky a',
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'キュ/ ky u',
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'キョ/ ky o',
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'シャ/ sh a',
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'シュ/ sh u',
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'シェ/ sh e',
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'ショ/ sh o',
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'チャ/ ch a',
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'チュ/ ch u',
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'チェ/ ch e',
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'チョ/ ch o',
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'トゥ/ t u',
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'トャ/ ty a',
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'トュ/ ty u',
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'トョ/ ty o',
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'ドァ/ d o a',
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'ドゥ/ d u',
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'ドャ/ dy a',
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'ドュ/ dy u',
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'ドョ/ dy o',
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'ドォ/ d o:',
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'ニャ/ ny a',
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'ニュ/ ny u',
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'ニョ/ ny o',
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'ヒャ/ hy a',
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'ヒュ/ hy u',
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'ヒョ/ hy o',
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'ミャ/ my a',
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'ミュ/ my u',
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'ミョ/ my o',
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'リャ/ ry a',
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'リュ/ ry u',
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'リョ/ ry o',
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'ギャ/ gy a',
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'ギュ/ gy u',
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'ギョ/ gy o',
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'ヂェ/ j e',
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'ヂャ/ j a',
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'ヂュ/ j u',
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'ヂョ/ j o',
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'ジェ/ j e',
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'ジャ/ j a',
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'ジュ/ j u',
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'ジョ/ j o',
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'ビャ/ by a',
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'ビュ/ by u',
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'ビョ/ by o',
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'ピャ/ py a',
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'ピュ/ py u',
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'ピョ/ py o',
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'ウァ/ u a',
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'ウィ/ w i',
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'ウェ/ w e',
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'ウォ/ w o',
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'ファ/ f a',
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'フィ/ f i',
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'フゥ/ f u',
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'フャ/ hy a',
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'フュ/ hy u',
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'フョ/ hy o',
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'フェ/ f e',
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'フォ/ f o',
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'ヴァ/ b a',
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'ヴィ/ b i',
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'ヴェ/ b e',
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'ヴォ/ b o',
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'ヴュ/ by u',
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# Conversion of 1 letter
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'ア/ a',
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'イ/ i',
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'ウ/ u',
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'エ/ e',
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'オ/ o',
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'カ/ k a',
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'キ/ k i',
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'ク/ k u',
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'ケ/ k e',
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'コ/ k o',
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'サ/ s a',
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'シ/ sh i',
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'ス/ s u',
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'セ/ s e',
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'ソ/ s o',
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'タ/ t a',
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'チ/ ch i',
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'ツ/ ts u',
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'テ/ t e',
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'ト/ t o',
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'ナ/ n a',
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'ニ/ n i',
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'ヌ/ n u',
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'ネ/ n e',
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'ノ/ n o',
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'ハ/ h a',
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'ヒ/ h i',
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'フ/ f u',
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'ヘ/ h e',
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'ホ/ h o',
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'マ/ m a',
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'ミ/ m i',
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'ム/ m u',
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'メ/ m e',
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'モ/ m o',
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'ラ/ r a',
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'リ/ r i',
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'ル/ r u',
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'レ/ r e',
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'ロ/ r o',
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'ガ/ g a',
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'ギ/ g i',
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'グ/ g u',
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'ゲ/ g e',
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'ゴ/ g o',
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'ザ/ z a',
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'ジ/ j i',
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'ズ/ z u',
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'ゼ/ z e',
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'ゾ/ z o',
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'ダ/ d a',
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'ヂ/ j i',
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'ヅ/ z u',
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'デ/ d e',
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'ド/ d o',
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'バ/ b a',
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'ビ/ b i',
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'ブ/ b u',
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'ベ/ b e',
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'ボ/ b o',
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'パ/ p a',
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'ピ/ p i',
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'プ/ p u',
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'ペ/ p e',
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'ポ/ p o',
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'ヤ/ y a',
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'ユ/ y u',
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'ヨ/ y o',
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'ワ/ w a',
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'ヰ/ i',
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'ヱ/ e',
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'ヲ/ o',
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'ン/ N',
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'ッ/ q',
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'ヴ/ b u',
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'ー/:',
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# Try converting broken text
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'ァ/ a',
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'ィ/ i',
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'ゥ/ u',
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'ェ/ e',
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'ォ/ o',
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'ヮ/ w a',
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'ォ/ o',
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# Symbols
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'、/ ,',
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'。/ .',
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'！/ !',
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'？/ ?',
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'・/ ,'
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]
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_COLON_RX = re.compile(':+')
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_REJECT_RX = re.compile('[^ a-zA-Z:,.?]')
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def _makerulemap():
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l = [tuple(x.split('/')) for x in _CONVRULES]
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return tuple(
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{k: v for k, v in l if len(k) == i}
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for i in (1, 2)
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)
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_RULEMAP1, _RULEMAP2 = _makerulemap()
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def kata2phoneme(text: str) -> str:
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"""Convert katakana text to phonemes.
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"""
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text = text.strip()
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res = ''
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while text:
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if len(text) >= 2:
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x = _RULEMAP2.get(text[:2])
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if x is not None:
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text = text[2:]
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res += x
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continue
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x = _RULEMAP1.get(text[0])
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if x is not None:
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text = text[1:]
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res += x
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continue
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res += ' ' + text[0]
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text = text[1:]
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res = _COLON_RX.sub(':', res)
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return res[1:]
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_KATAKANA = ''.join(chr(ch) for ch in range(ord('ァ'), ord('ン') + 1))
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_HIRAGANA = ''.join(chr(ch) for ch in range(ord('ぁ'), ord('ん') + 1))
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_HIRA2KATATRANS = str.maketrans(_HIRAGANA, _KATAKANA)
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def hira2kata(text: str) -> str:
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text = text.translate(_HIRA2KATATRANS)
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return text.replace('う゛', 'ヴ')
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_SYMBOL_TOKENS = set(list('・、。？！'))
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_NO_YOMI_TOKENS = set(list('「」『』―（）［］[] …'))
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_TAGGER = MeCab.Tagger()
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def text2kata(text: str) -> str:
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parsed = _TAGGER.parse(text)
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res = []
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for line in parsed.split('\n'):
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if line == 'EOS':
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break
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parts = line.split('\t')
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word, yomi = parts[0], parts[1]
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if yomi:
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res.append(yomi)
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else:
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if word in _SYMBOL_TOKENS:
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res.append(word)
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elif word in ('っ', 'ッ'):
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res.append('ッ')
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elif word in _NO_YOMI_TOKENS:
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pass
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else:
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res.append(word)
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return hira2kata(''.join(res))
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def japanese_text_to_phonemes(text: str) -> str:
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"""Convert Japanese text to phonemes.
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"""
|
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res = text2kata(text)
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res = kata2phoneme(res)
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return res.replace(' ', '')
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@ -0,0 +1,23 @@
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#!/bin/bash
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# take the scripts's parent's directory to prefix all the output paths.
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RUN_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )"
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CORPUS=kokoro-speech-v1_1-small
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echo $RUN_DIR
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if [ \! -d $RUN_DIR/$CORPUS ] ; then
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echo "$RUN_DIR/$CORPUS doesn't exist."
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echo "Follow the instruction of https://github.com/kaiidams/Kokoro-Speech-Dataset to make the corpus."
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exit 1
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fi
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# create train-val splits
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shuf $RUN_DIR/$CORPUS/metadata.csv > $RUN_DIR/$CORPUS/metadata_shuf.csv
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head -n 8000 $RUN_DIR/$CORPUS/metadata_shuf.csv > $RUN_DIR/$CORPUS/metadata_train.csv
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tail -n 812 $RUN_DIR/$CORPUS/metadata_shuf.csv > $RUN_DIR/$CORPUS/metadata_val.csv
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# compute dataset mean and variance for normalization
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python TTS/bin/compute_statistics.py $RUN_DIR/tacotron2-DDC.json $RUN_DIR/scale_stats.npy --data_path $RUN_DIR/$CORPUS/wavs/
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# training ....
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# change the GPU id if needed
|
||||
CUDA_VISIBLE_DEVICES="0" python TTS/bin/train_tacotron.py --config_path $RUN_DIR/tacotron2-DDC.json \
|
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--coqpit.output_path $RUN_DIR \
|
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--coqpit.datasets.0.path $RUN_DIR/$CORPUS \
|
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--coqpit.audio.stats_path $RUN_DIR/scale_stats.npy \
|
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--coqpit.phoneme_cache_path $RUN_DIR/phoneme_cache \
|
||||
|
|
@ -0,0 +1,125 @@
|
|||
{
|
||||
"datasets": [
|
||||
{
|
||||
"name": "kokoro",
|
||||
"path": "DEFINE THIS",
|
||||
"meta_file_train": "metadata.csv",
|
||||
"meta_file_val": null
|
||||
}
|
||||
],
|
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"audio": {
|
||||
"fft_size": 1024,
|
||||
"win_length": 1024,
|
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"hop_length": 256,
|
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"frame_length_ms": null,
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"frame_shift_ms": null,
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"sample_rate": 22050,
|
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"preemphasis": 0.0,
|
||||
"ref_level_db": 20,
|
||||
"do_trim_silence": true,
|
||||
"trim_db": 60,
|
||||
"power": 1.5,
|
||||
"griffin_lim_iters": 60,
|
||||
"num_mels": 80,
|
||||
"mel_fmin": 50.0,
|
||||
"mel_fmax": 7600.0,
|
||||
"spec_gain": 1,
|
||||
"signal_norm": true,
|
||||
"min_level_db": -100,
|
||||
"symmetric_norm": true,
|
||||
"max_norm": 4.0,
|
||||
"clip_norm": true,
|
||||
"stats_path": "scale_stats.npy"
|
||||
},
|
||||
"gst":{
|
||||
"gst_style_input": null,
|
||||
|
||||
|
||||
|
||||
"gst_embedding_dim": 512,
|
||||
"gst_num_heads": 4,
|
||||
"gst_style_tokens": 10,
|
||||
"gst_use_speaker_embedding": false
|
||||
},
|
||||
"model": "Tacotron2",
|
||||
"run_name": "kokoro-ddc",
|
||||
"run_description": "tacotron2 with DDC and differential spectral loss.",
|
||||
"batch_size": 32,
|
||||
"eval_batch_size": 16,
|
||||
"mixed_precision": true,
|
||||
"distributed": {
|
||||
"backend": "nccl",
|
||||
"url": "tcp:\/\/localhost:54321"
|
||||
},
|
||||
"reinit_layers": [],
|
||||
"loss_masking": true,
|
||||
"decoder_loss_alpha": 0.5,
|
||||
"postnet_loss_alpha": 0.25,
|
||||
"postnet_diff_spec_alpha": 0.25,
|
||||
"decoder_diff_spec_alpha": 0.25,
|
||||
"decoder_ssim_alpha": 0.5,
|
||||
"postnet_ssim_alpha": 0.25,
|
||||
"ga_alpha": 5.0,
|
||||
"stopnet_pos_weight": 15.0,
|
||||
"run_eval": true,
|
||||
"test_delay_epochs": 10,
|
||||
"test_sentences_file": null,
|
||||
"noam_schedule": false,
|
||||
"grad_clip": 1.0,
|
||||
"epochs": 1000,
|
||||
"lr": 0.0001,
|
||||
"wd": 0.000001,
|
||||
"warmup_steps": 4000,
|
||||
"seq_len_norm": false,
|
||||
"memory_size": -1,
|
||||
"prenet_type": "original",
|
||||
"prenet_dropout": true,
|
||||
"attention_type": "original",
|
||||
"windowing": false,
|
||||
"use_forward_attn": false,
|
||||
"forward_attn_mask": false,
|
||||
"transition_agent": false,
|
||||
"location_attn": true,
|
||||
"bidirectional_decoder": false,
|
||||
"double_decoder_consistency": true,
|
||||
"ddc_r": 7,
|
||||
"attention_heads": 4,
|
||||
"attention_norm": "sigmoid",
|
||||
"r": 7,
|
||||
"gradual_training": [[0, 7, 64], [1, 5, 64], [50000, 3, 32], [130000, 2, 32], [290000, 1, 32]],
|
||||
"stopnet": true,
|
||||
"separate_stopnet": true,
|
||||
"print_step": 25,
|
||||
"tb_plot_step": 100,
|
||||
"print_eval": false,
|
||||
"save_step": 10000,
|
||||
"checkpoint": true,
|
||||
"keep_all_best": false,
|
||||
"keep_after": 10000,
|
||||
"tb_model_param_stats": false,
|
||||
"text_cleaner": "basic_cleaners",
|
||||
"enable_eos_bos_chars": false,
|
||||
"num_loader_workers": 4,
|
||||
"num_val_loader_workers": 4,
|
||||
"batch_group_size": 4,
|
||||
"min_seq_len": 6,
|
||||
"max_seq_len": 153,
|
||||
"compute_input_seq_cache": false,
|
||||
"use_noise_augment": true,
|
||||
"output_path": "DEFINE THIS",
|
||||
"phoneme_cache_path": "DEFINE THIS",
|
||||
"use_phonemes": true,
|
||||
"phoneme_language": "ja-jp",
|
||||
"characters": {
|
||||
"pad": "_",
|
||||
"eos": "~",
|
||||
"bos": "^",
|
||||
"characters": "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz!'(),-.:;? ",
|
||||
"punctuations": "!'(),-.:;? ",
|
||||
"phonemes": "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz"
|
||||
},
|
||||
"use_speaker_embedding": false,
|
||||
"use_gst": false,
|
||||
"use_external_speaker_embedding_file": false,
|
||||
"external_speaker_embedding_file": "../../speakers-vctk-en.json"
|
||||
}
|
||||
|
|
@ -19,3 +19,5 @@ numba==0.52
|
|||
umap-learn==0.4.6
|
||||
anyascii
|
||||
coqpit
|
||||
mecab-python3
|
||||
unidic-lite
|
||||
|
|
|
|||
|
|
@ -0,0 +1,22 @@
|
|||
import unittest
|
||||
from TTS.tts.utils.text.japanese.phonemizer import japanese_text_to_phonemes
|
||||
|
||||
_TEST_CASES = '''
|
||||
どちらに行きますか？/dochiraniikimasuka?
|
||||
今日は温泉に、行きます。/kyo:waoNseNni,ikimasu.
|
||||
「A」から「Z」までです。/AkaraZmadedesu.
|
||||
そうですね！/so:desune!
|
||||
クジラは哺乳類です。/kujirawahonyu:ruidesu.
|
||||
ヴィディオを見ます。/bidioomimasu.
|
||||
ky o: w a o N s e N n i , i k i m a s u ./kyo:waoNseNni,ikimasu.
|
||||
'''
|
||||
|
||||
class TestText(unittest.TestCase):
|
||||
|
||||
def test_japanese_text_to_phonemes(self):
|
||||
for line in _TEST_CASES.strip().split('\n'):
|
||||
text, phone = line.split('/')
|
||||
self.assertEqual(japanese_text_to_phonemes(text), phone)
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
Loading…
Reference in New Issue