This commit is contained in:
killua committed 2024-06-09 22:54:13 +08:00
commit 4c255ebd59
51 files changed
+3424

No files matched your search

+19
View File
@@ -0,0 +1,19 @@
Copyright (c) 2017 Keith Ito
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
+57
View File
@@ -0,0 +1,57 @@
""" from https://github.com/keithito/tacotron """
from . import cleaners
from .symbols import symbols
# Mappings from symbol to numeric ID and vice versa:
_symbol_to_id = {s: i for i, s in enumerate(symbols)}
_id_to_symbol = {i: s for i, s in enumerate(symbols)}
def text_to_sequence(text, symbols, cleaner_names):
'''Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
Args:
text: string to convert to a sequence
cleaner_names: names of the cleaner functions to run the text through
Returns:
List of integers corresponding to the symbols in the text
'''
_symbol_to_id = {s: i for i, s in enumerate(symbols)}
sequence = []
clean_text = _clean_text(text, cleaner_names)
for symbol in clean_text:
if symbol not in _symbol_to_id.keys():
continue
symbol_id = _symbol_to_id[symbol]
sequence += [symbol_id]
return sequence, clean_text
def cleaned_text_to_sequence(cleaned_text):
'''Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
Args:
text: string to convert to a sequence
Returns:
List of integers corresponding to the symbols in the text
'''
sequence = [_symbol_to_id[symbol] for symbol in cleaned_text if symbol in _symbol_to_id.keys()]
return sequence
def sequence_to_text(sequence):
'''Converts a sequence of IDs back to a string'''
result = ''
for symbol_id in sequence:
s = _id_to_symbol[symbol_id]
result += s
return result
def _clean_text(text, cleaner_names):
for name in cleaner_names:
cleaner = getattr(cleaners, name)
if not cleaner:
raise Exception('Unknown cleaner: %s' % name)
text = cleaner(text)
return text
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
+475
View File
@@ -0,0 +1,475 @@
""" 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 pyopenjtalk
from jamo import h2j, j2hcj
from pypinyin import lazy_pinyin, BOPOMOFO
import jieba, cn2an
# 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')
]]
# List of (Latin alphabet, bopomofo) pairs:
_latin_to_bopomofo = [(re.compile('%s' % x[0], re.IGNORECASE), x[1]) for x in [
('a', 'ㄟˉ'),
('b', 'ㄅㄧˋ'),
('c', 'ㄙㄧˉ'),
('d', 'ㄉㄧˋ'),
('e', 'ㄧˋ'),
('f', 'ㄝˊㄈㄨˋ'),
('g', 'ㄐㄧˋ'),
('h', 'ㄝˇㄑㄩˋ'),
('i', 'ㄞˋ'),
('j', 'ㄐㄟˋ'),
('k', 'ㄎㄟˋ'),
('l', 'ㄝˊㄛˋ'),
('m', 'ㄝˊㄇㄨˋ'),
('n', 'ㄣˉ'),
('o', 'ㄡˉ'),
('p', 'ㄆㄧˉ'),
('q', 'ㄎㄧㄡˉ'),
('r', 'ㄚˋ'),
('s', 'ㄝˊㄙˋ'),
('t', 'ㄊㄧˋ'),
('u', 'ㄧㄡˉ'),
('v', 'ㄨㄧˉ'),
('w', 'ㄉㄚˋㄅㄨˋㄌㄧㄡˋ'),
('x', 'ㄝˉㄎㄨˋㄙˋ'),
('y', 'ㄨㄞˋ'),
('z', 'ㄗㄟˋ')
]]
# List of (bopomofo, romaji) pairs:
_bopomofo_to_romaji = [(re.compile('%s' % x[0], re.IGNORECASE), x[1]) for x in [
('ㄅㄛ', 'p⁼wo'),
('ㄆㄛ', 'pʰwo'),
('ㄇㄛ', 'mwo'),
('ㄈㄛ', 'fwo'),
('ㄅ', 'p⁼'),
('ㄆ', 'pʰ'),
('ㄇ', 'm'),
('ㄈ', 'f'),
('ㄉ', 't⁼'),
('ㄊ', 'tʰ'),
('ㄋ', 'n'),
('ㄌ', 'l'),
('ㄍ', 'k⁼'),
('ㄎ', 'kʰ'),
('ㄏ', 'h'),
('ㄐ', 'ʧ⁼'),
('ㄑ', 'ʧʰ'),
('ㄒ', 'ʃ'),
('ㄓ', 'ʦ`⁼'),
('ㄔ', 'ʦ`ʰ'),
('ㄕ', 's`'),
('ㄖ', 'ɹ`'),
('ㄗ', 'ʦ⁼'),
('ㄘ', 'ʦʰ'),
('ㄙ', 's'),
('ㄚ', 'a'),
('ㄛ', 'o'),
('ㄜ', 'ə'),
('ㄝ', 'e'),
('ㄞ', 'ai'),
('ㄟ', 'ei'),
('ㄠ', 'au'),
('ㄡ', 'ou'),
('ㄧㄢ', 'yeNN'),
('ㄢ', 'aNN'),
('ㄧㄣ', 'iNN'),
('ㄣ', 'əNN'),
('ㄤ', 'aNg'),
('ㄧㄥ', 'iNg'),
('ㄨㄥ', 'uNg'),
('ㄩㄥ', 'yuNg'),
('ㄥ', 'əNg'),
('ㄦ', 'əɻ'),
('ㄧ', 'i'),
('ㄨ', 'u'),
('ㄩ', 'ɥ'),
('ˉ', '→'),
('ˊ', '↑'),
('ˇ', '↓↑'),
('ˋ', '↓'),
('˙', ''),
(',', ','),
('。', '.'),
('!', '!'),
('?', '?'),
('—', '-')
]]
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 japanese_to_romaji_with_accent(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<len(marks):
text += unidecode(marks[i]).replace(' ','')
return 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 number_to_chinese(text):
numbers = re.findall(r'\d+(?:\.?\d+)?', text)
for number in numbers:
text = text.replace(number, cn2an.an2cn(number),1)
return text
def chinese_to_bopomofo(text):
text=text.replace('、',',').replace(';',',').replace(':',',')
words=jieba.lcut(text,cut_all=False)
text=''
for word in words:
bopomofos=lazy_pinyin(word,BOPOMOFO)
if not re.search('[\u4e00-\u9fff]',word):
text+=word
continue
for i in range(len(bopomofos)):
if re.match('[\u3105-\u3129]',bopomofos[i][-1]):
bopomofos[i]+='ˉ'
if text!='':
text+=' '
text+=''.join(bopomofos)
return text
def latin_to_bopomofo(text):
for regex, replacement in _latin_to_bopomofo:
text = re.sub(regex, replacement, text)
return text
def bopomofo_to_romaji(text):
for regex, replacement in _bopomofo_to_romaji:
text = re.sub(regex, replacement, text)
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):
text=japanese_to_romaji_with_accent(text)
if re.match('[A-Za-z]',text[-1]):
text += '.'
return text
def japanese_cleaners2(text):
return japanese_cleaners(text).replace('ts','ʦ').replace('...','…')
def korean_cleaners(text):
'''Pipeline for Korean text'''
text = latin_to_hangul(text)
text = number_to_hangul(text)
text = j2hcj(h2j(text))
text = divide_hangul(text)
if re.match('[\u3131-\u3163]',text[-1]):
text += '.'
return text
def chinese_cleaners(text):
'''Pipeline for Chinese text'''
text=number_to_chinese(text)
text=chinese_to_bopomofo(text)
text=latin_to_bopomofo(text)
if re.match('[ˉˊˇˋ˙]',text[-1]):
text += '。'
return text
def zh_ja_mixture_cleaners(text):
chinese_texts=re.findall(r'\[ZH\].*?\[ZH\]',text)
japanese_texts=re.findall(r'\[JA\].*?\[JA\]',text)
for chinese_text in chinese_texts:
cleaned_text=number_to_chinese(chinese_text[4:-4])
cleaned_text=chinese_to_bopomofo(cleaned_text)
cleaned_text=latin_to_bopomofo(cleaned_text)
cleaned_text=bopomofo_to_romaji(cleaned_text)
cleaned_text=re.sub('i[aoe]',lambda x:'y'+x.group(0)[1:],cleaned_text)
cleaned_text=re.sub('u[aoəe]',lambda x:'w'+x.group(0)[1:],cleaned_text)
cleaned_text=re.sub('([ʦsɹ]`[⁼ʰ]?)([→↓↑]+)',lambda x:x.group(1)+'ɹ`'+x.group(2),cleaned_text).replace('ɻ','ɹ`')
cleaned_text=re.sub('([ʦs][⁼ʰ]?)([→↓↑]+)',lambda x:x.group(1)+'ɹ'+x.group(2),cleaned_text)
text = text.replace(chinese_text,cleaned_text+' ',1)
for japanese_text in japanese_texts:
cleaned_text=japanese_to_romaji_with_accent(japanese_text[4:-4]).replace('ts','ʦ').replace('u','ɯ').replace('...','…')
text = text.replace(japanese_text,cleaned_text+' ',1)
text=text[:-1]
if re.match('[A-Za-zɯɹəɥ→↓↑]',text[-1]):
text += '.'
return text
+39
View File
@@ -0,0 +1,39 @@
'''
Defines the set of symbols used in text input to the model.
'''
'''# japanese_cleaners
_pad = '_'
_punctuation = ',.!?-'
_letters = 'AEINOQUabdefghijkmnoprstuvwyzʃʧ↓↑ '
'''
'''# japanese_cleaners2
_pad = '_'
_punctuation = ',.!?-~…'
_letters = 'AEINOQUabdefghijkmnoprstuvwyzʃʧʦ↓↑ '
'''
'''# korean_cleaners
_pad = '_'
_punctuation = ',.!?…~'
_letters = 'ㄱㄴㄷㄹㅁㅂㅅㅇㅈㅊㅋㅌㅍㅎㄲㄸㅃㅆㅉㅏㅓㅗㅜㅡㅣㅐㅔ '
'''
'''# chinese_cleaners
_pad = '_'
_punctuation = ',。!?—…'
_letters = 'ㄅㄆㄇㄈㄉㄊㄋㄌㄍㄎㄏㄐㄑㄒㄓㄔㄕㄖㄗㄘㄙㄚㄛㄜㄝㄞㄟㄠㄡㄢㄣㄤㄥㄦㄧㄨㄩˉˊˇˋ˙ '
'''
# zh_ja_mixture_cleaners
_pad = '_'
_punctuation = ',.!?-~…'
_letters = 'AEINOQUabdefghijklmnoprstuvwyzʃʧʦɯɹəɥ⁼ʰ`→↓↑ '
# Export all symbols:
symbols = [_pad] + list(_punctuation) + list(_letters)
# Special symbol ids
SPACE_ID = symbols.index(" ")