""" from https://github.com/keithito/tacotron """ ''' Cleaners are transformations that run over the input text at both training and eval time. Cleaners can be selected by passing a comma-delimited list of cleaner names as the "cleaners" hyperparameter. Some cleaners are English-specific. You'll typically want to use: 1. "english_cleaners" for English text 2. "transliteration_cleaners" for non-English text that can be transliterated to ASCII using the Unidecode library (https://pypi.python.org/pypi/Unidecode) 3. "basic_cleaners" if you do not want to transliterate (in this case, you should also update the symbols in symbols.py to match your data). ''' import re from unidecode import unidecode import jieba import pyopenjtalk from jamo import h2j, j2hcj from pypinyin import lazy_pinyin,BOPOMOFO # This is a list of Korean classifiers preceded by pure Korean numerals. _korean_classifiers = '군데 권 개 그루 닢 대 두 마리 모 모금 뭇 발 발짝 방 번 벌 보루 살 수 술 시 쌈 움큼 정 짝 채 척 첩 축 켤레 톨 통' # Regular expression matching whitespace: _whitespace_re = re.compile(r'\s+') # Regular expression matching Japanese without punctuation marks: _japanese_characters = re.compile(r'[A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]') # Regular expression matching non-Japanese characters or punctuation marks: _japanese_marks = re.compile(r'[^A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]') # List of (regular expression, replacement) pairs for abbreviations: _abbreviations = [(re.compile('\\b%s\\.' % x[0], re.IGNORECASE), x[1]) for x in [ ('mrs', 'misess'), ('mr', 'mister'), ('dr', 'doctor'), ('st', 'saint'), ('co', 'company'), ('jr', 'junior'), ('maj', 'major'), ('gen', 'general'), ('drs', 'doctors'), ('rev', 'reverend'), ('lt', 'lieutenant'), ('hon', 'honorable'), ('sgt', 'sergeant'), ('capt', 'captain'), ('esq', 'esquire'), ('ltd', 'limited'), ('col', 'colonel'), ('ft', 'fort'), ]] # List of (hangul, hangul divided) pairs: _hangul_divided = [(re.compile('%s' % x[0]), x[1]) for x in [ ('ㄳ', 'ㄱㅅ'), ('ㄵ', 'ㄴㅈ'), ('ㄶ', 'ㄴㅎ'), ('ㄺ', 'ㄹㄱ'), ('ㄻ', 'ㄹㅁ'), ('ㄼ', 'ㄹㅂ'), ('ㄽ', 'ㄹㅅ'), ('ㄾ', 'ㄹㅌ'), ('ㄿ', 'ㄹㅍ'), ('ㅀ', 'ㄹㅎ'), ('ㅄ', 'ㅂㅅ'), ('ㅘ', 'ㅗㅏ'), ('ㅙ', 'ㅗㅐ'), ('ㅚ', 'ㅗㅣ'), ('ㅝ', 'ㅜㅓ'), ('ㅞ', 'ㅜㅔ'), ('ㅟ', 'ㅜㅣ'), ('ㅢ', 'ㅡㅣ'), ('ㅑ', 'ㅣㅏ'), ('ㅒ', 'ㅣㅐ'), ('ㅕ', 'ㅣㅓ'), ('ㅖ', 'ㅣㅔ'), ('ㅛ', 'ㅣㅗ'), ('ㅠ', 'ㅣㅜ') ]] # List of (Latin alphabet, hangul) pairs: _latin_to_hangul = [(re.compile('%s' % x[0], re.IGNORECASE), x[1]) for x in [ ('a', '에이'), ('b', '비'), ('c', '시'), ('d', '디'), ('e', '이'), ('f', '에프'), ('g', '지'), ('h', '에이치'), ('i', '아이'), ('j', '제이'), ('k', '케이'), ('l', '엘'), ('m', '엠'), ('n', '엔'), ('o', '오'), ('p', '피'), ('q', '큐'), ('r', '아르'), ('s', '에스'), ('t', '티'), ('u', '유'), ('v', '브이'), ('w', '더블유'), ('x', '엑스'), ('y', '와이'), ('z', '제트') ]] def expand_abbreviations(text): for regex, replacement in _abbreviations: text = re.sub(regex, replacement, text) return text def lowercase(text): return text.lower() def collapse_whitespace(text): return re.sub(_whitespace_re, ' ', text) def convert_to_ascii(text): return unidecode(text) def latin_to_hangul(text): for regex, replacement in _latin_to_hangul: text = re.sub(regex, replacement, text) return text def divide_hangul(text): for regex, replacement in _hangul_divided: text = re.sub(regex, replacement, text) return text def hangul_number(num, sino=True): '''Reference https://github.com/Kyubyong/g2pK''' num = re.sub(',', '', num) if num == '0': return '영' if not sino and num == '20': return '스무' digits = '123456789' names = '일이삼사오육칠팔구' digit2name = {d: n for d, n in zip(digits, names)} modifiers = '한 두 세 네 다섯 여섯 일곱 여덟 아홉' decimals = '열 스물 서른 마흔 쉰 예순 일흔 여든 아흔' digit2mod = {d: mod for d, mod in zip(digits, modifiers.split())} digit2dec = {d: dec for d, dec in zip(digits, decimals.split())} spelledout = [] for i, digit in enumerate(num): i = len(num) - i - 1 if sino: if i == 0: name = digit2name.get(digit, '') elif i == 1: name = digit2name.get(digit, '') + '십' name = name.replace('일십', '십') else: if i == 0: name = digit2mod.get(digit, '') elif i == 1: name = digit2dec.get(digit, '') if digit == '0': if i % 4 == 0: last_three = spelledout[-min(3, len(spelledout)):] if ''.join(last_three) == '': spelledout.append('') continue else: spelledout.append('') continue if i == 2: name = digit2name.get(digit, '') + '백' name = name.replace('일백', '백') elif i == 3: name = digit2name.get(digit, '') + '천' name = name.replace('일천', '천') elif i == 4: name = digit2name.get(digit, '') + '만' name = name.replace('일만', '만') elif i == 5: name = digit2name.get(digit, '') + '십' name = name.replace('일십', '십') elif i == 6: name = digit2name.get(digit, '') + '백' name = name.replace('일백', '백') elif i == 7: name = digit2name.get(digit, '') + '천' name = name.replace('일천', '천') elif i == 8: name = digit2name.get(digit, '') + '억' elif i == 9: name = digit2name.get(digit, '') + '십' elif i == 10: name = digit2name.get(digit, '') + '백' elif i == 11: name = digit2name.get(digit, '') + '천' elif i == 12: name = digit2name.get(digit, '') + '조' elif i == 13: name = digit2name.get(digit, '') + '십' elif i == 14: name = digit2name.get(digit, '') + '백' elif i == 15: name = digit2name.get(digit, '') + '천' spelledout.append(name) return ''.join(elem for elem in spelledout) def number_to_hangul(text): '''Reference https://github.com/Kyubyong/g2pK''' tokens = set(re.findall(r'(\d[\d,]*)([\uac00-\ud71f]+)', text)) for token in tokens: num, classifier = token if classifier[:2] in _korean_classifiers or classifier[0] in _korean_classifiers: spelledout = hangul_number(num, sino=False) else: spelledout = hangul_number(num, sino=True) text = text.replace(f'{num}{classifier}', f'{spelledout}{classifier}') # digit by digit for remaining digits digits = '0123456789' names = '영일이삼사오육칠팔구' for d, n in zip(digits, names): text = text.replace(d, n) return text def basic_cleaners(text): '''Basic pipeline that lowercases and collapses whitespace without transliteration.''' text = lowercase(text) text = collapse_whitespace(text) return text def transliteration_cleaners(text): '''Pipeline for non-English text that transliterates to ASCII.''' text = convert_to_ascii(text) text = lowercase(text) text = collapse_whitespace(text) return text def japanese_cleaners(text): '''Pipeline for notating accent in Japanese text. Reference https://r9y9.github.io/ttslearn/latest/notebooks/ch10_Recipe-Tacotron.html''' sentences = re.split(_japanese_marks, text) marks = re.findall(_japanese_marks, text) text = '' for i, sentence in enumerate(sentences): if re.match(_japanese_characters, sentence): if text!='': text+=' ' labels = pyopenjtalk.extract_fullcontext(sentence) for n, label in enumerate(labels): phoneme = re.search(r'\-([^\+]*)\+', label).group(1) if phoneme not in ['sil','pau']: text += phoneme.replace('ch','ʧ').replace('sh','ʃ').replace('cl','Q') else: continue n_moras = int(re.search(r'/F:(\d+)_', label).group(1)) a1 = int(re.search(r"/A:(\-?[0-9]+)\+", label).group(1)) a2 = int(re.search(r"\+(\d+)\+", label).group(1)) a3 = int(re.search(r"\+(\d+)/", label).group(1)) if re.search(r'\-([^\+]*)\+', labels[n + 1]).group(1) in ['sil','pau']: a2_next=-1 else: a2_next = int(re.search(r"\+(\d+)\+", labels[n + 1]).group(1)) # Accent phrase boundary if a3 == 1 and a2_next == 1: text += ' ' # Falling elif a1 == 0 and a2_next == a2 + 1 and a2 != n_moras: text += '↓' # Rising elif a2 == 1 and a2_next == 2: text += '↑' if i