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Browse files- text/LICENSE +19 -0
- text/__init__.py +32 -0
- text/cleaners.py +17 -0
- text/japanese.py +132 -0
text/LICENSE
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Copyright (c) 2017 Keith Ito
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in
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all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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THE SOFTWARE.
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text/__init__.py
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""" from https://github.com/keithito/tacotron """
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from text import cleaners
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def text_to_sequence(text, symbols, cleaner_names):
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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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text: string to convert to a sequence
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cleaner_names: names of the cleaner functions to run the text through
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Returns:
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List of integers corresponding to the symbols in the text
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'''
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_symbol_to_id = {s: i for i, s in enumerate(symbols)}
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sequence = []
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clean_text = _clean_text(text, cleaner_names)
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for symbol in clean_text:
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if symbol not in _symbol_to_id.keys():
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continue
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symbol_id = _symbol_to_id[symbol]
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sequence += [symbol_id]
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return sequence
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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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text/cleaners.py
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import re
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def japanese_cleaners(text):
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from text.japanese import japanese_to_romaji_with_accent
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text = japanese_to_romaji_with_accent(text)
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if len(text) == 0 or re.match('[A-Za-z]', text[-1]):
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text += '.'
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return text
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def japanese_cleaners2(text):
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text = text.replace('・・・', '…').replace('・', ' ')
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text = japanese_cleaners(text).replace('ts', 'ʦ').replace('...', '…') \
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.replace('(', '').replace(')', '') \
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.replace('[', '').replace(']', '') \
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.replace('*', ' ').replace('{', '').replace('}', '')
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return text
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text/japanese.py
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import re
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from unidecode import unidecode
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import pyopenjtalk
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# Regular expression matching Japanese without punctuation marks:
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_japanese_characters = re.compile(
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r'[A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]')
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# Regular expression matching non-Japanese characters or punctuation marks:
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_japanese_marks = re.compile(
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r'[^A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]')
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# List of (symbol, Japanese) pairs for marks:
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_symbols_to_japanese = [(re.compile('%s' % x[0]), x[1]) for x in [
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('%', 'パーセント')
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]]
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# List of (romaji, ipa) pairs for marks:
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_romaji_to_ipa = [(re.compile('%s' % x[0], re.IGNORECASE), x[1]) for x in [
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('ts', 'ʦ'),
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('u', 'ɯ'),
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('...', '…'),
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('j', 'ʥ'),
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('y', 'j'),
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('ni', 'n^i'),
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('nj', 'n^'),
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('hi', 'çi'),
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('hj', 'ç'),
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('f', 'ɸ'),
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('I', 'i*'),
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('U', 'ɯ*'),
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('r', 'ɾ')
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]]
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# Dictinary of (consonant, sokuon) pairs:
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_real_sokuon = {
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'k': 'k#',
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'g': 'k#',
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't': 't#',
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'd': 't#',
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'ʦ': 't#',
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'ʧ': 't#',
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'ʥ': 't#',
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'j': 't#',
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's': 's',
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'ʃ': 's',
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'p': 'p#',
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'b': 'p#'
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}
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# Dictinary of (consonant, hatsuon) pairs:
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_real_hatsuon = {
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'p': 'm',
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'b': 'm',
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'm': 'm',
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't': 'n',
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'd': 'n',
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'n': 'n',
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'ʧ': 'n^',
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'ʥ': 'n^',
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'k': 'ŋ',
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'g': 'ŋ'
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}
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def symbols_to_japanese(text):
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for regex, replacement in _symbols_to_japanese:
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text = re.sub(regex, replacement, text)
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return text
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def japanese_to_romaji_with_accent(text):
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'''Reference https://r9y9.github.io/ttslearn/latest/notebooks/ch10_Recipe-Tacotron.html'''
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text = symbols_to_japanese(text)
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sentences = re.split(_japanese_marks, text)
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marks = re.findall(_japanese_marks, text)
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text = ''
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for i, sentence in enumerate(sentences):
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if re.match(_japanese_characters, sentence):
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if text != '':
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text += ' '
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labels = pyopenjtalk.extract_fullcontext(sentence)
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for n, label in enumerate(labels):
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phoneme = re.search(r'\-([^\+]*)\+', label).group(1)
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if phoneme not in ['sil', 'pau']:
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text += phoneme.replace('ch', 'ʧ').replace('sh',
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'ʃ').replace('cl', 'Q')
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else:
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continue
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# n_moras = int(re.search(r'/F:(\d+)_', label).group(1))
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a1 = int(re.search(r"/A:(\-?[0-9]+)\+", label).group(1))
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a2 = int(re.search(r"\+(\d+)\+", label).group(1))
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a3 = int(re.search(r"\+(\d+)/", label).group(1))
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if re.search(r'\-([^\+]*)\+', labels[n + 1]).group(1) in ['sil', 'pau']:
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a2_next = -1
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else:
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a2_next = int(
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re.search(r"\+(\d+)\+", labels[n + 1]).group(1))
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# Accent phrase boundary
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if a3 == 1 and a2_next == 1:
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text += ' '
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# Falling
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elif a1 == 0 and a2_next == a2 + 1:
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text += '↓'
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# Rising
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elif a2 == 1 and a2_next == 2:
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text += '↑'
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if i < len(marks):
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text += unidecode(marks[i]).replace(' ', '')
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return text
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def get_real_sokuon(text):
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text=re.sub('Q[↑↓]*(.)',lambda x:_real_sokuon[x.group(1)]+x.group(0)[1:] if x.group(1) in _real_sokuon.keys() else x.group(0),text)
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return text
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def get_real_hatsuon(text):
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text=re.sub('N[↑↓]*(.)',lambda x:_real_hatsuon[x.group(1)]+x.group(0)[1:] if x.group(1) in _real_hatsuon.keys() else x.group(0),text)
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return text
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def japanese_to_ipa(text):
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text=japanese_to_romaji_with_accent(text)
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for regex, replacement in _romaji_to_ipa:
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text = re.sub(regex, replacement, text)
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text = re.sub(
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r'([A-Za-zɯ])\1+', lambda x: x.group(0)[0]+'ː'*(len(x.group(0))-1), text)
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text = get_real_sokuon(text)
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text = get_real_hatsuon(text)
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return text
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