zoengjyutgaai_tts / text /chinese2.py
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import os
import pdb
import re
import cn2an
from pypinyin import lazy_pinyin, Style
from pypinyin.contrib.tone_convert import to_normal, to_finals_tone3, to_initials, to_finals
from text.symbols import punctuation
from text.tone_sandhi import ToneSandhi
from text.zh_normalization.text_normlization import TextNormalizer
normalizer = lambda x: cn2an.transform(x, "an2cn")
current_file_path = os.path.dirname(__file__)
pinyin_to_symbol_map = {
line.split("\t")[0]: line.strip().split("\t")[1]
for line in open(os.path.join(current_file_path, "opencpop-strict.txt")).readlines()
}
import jieba_fast.posseg as psg
# is_g2pw_str = os.environ.get("is_g2pw", "True")##默认开启
# is_g2pw = False#True if is_g2pw_str.lower() == 'true' else False
is_g2pw = True#True if is_g2pw_str.lower() == 'true' else False
if is_g2pw:
print("当前使用g2pw进行拼音推理")
from text.g2pw import G2PWPinyin, correct_pronunciation
parent_directory = os.path.dirname(current_file_path)
g2pw = G2PWPinyin(model_dir="GPT_SoVITS/text/G2PWModel",model_source=os.environ.get("bert_path","GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large"),v_to_u=False, neutral_tone_with_five=True)
rep_map = {
":": ",",
";": ",",
",": ",",
"。": ".",
"!": "!",
"?": "?",
"\n": ".",
"·": ",",
"、": ",",
"...": "…",
"$": ".",
"/": ",",
"—": "-",
"~": "…",
"~":"…",
}
tone_modifier = ToneSandhi()
def replace_punctuation(text):
text = text.replace("嗯", "恩").replace("呣", "母")
pattern = re.compile("|".join(re.escape(p) for p in rep_map.keys()))
replaced_text = pattern.sub(lambda x: rep_map[x.group()], text)
replaced_text = re.sub(
r"[^\u4e00-\u9fa5" + "".join(punctuation) + r"]+", "", replaced_text
)
return replaced_text
def g2p(text):
pattern = r"(?<=[{0}])\s*".format("".join(punctuation))
sentences = [i for i in re.split(pattern, text) if i.strip() != ""]
phones, word2ph = _g2p(sentences)
return phones, word2ph
def _get_initials_finals(word):
initials = []
finals = []
orig_initials = lazy_pinyin(word, neutral_tone_with_five=True, style=Style.INITIALS)
orig_finals = lazy_pinyin(
word, neutral_tone_with_five=True, style=Style.FINALS_TONE3
)
for c, v in zip(orig_initials, orig_finals):
initials.append(c)
finals.append(v)
return initials, finals
must_erhua = {
"小院儿", "胡同儿", "范儿", "老汉儿", "撒欢儿", "寻老礼儿", "妥妥儿", "媳妇儿"
}
not_erhua = {
"虐儿", "为儿", "护儿", "瞒儿", "救儿", "替儿", "有儿", "一儿", "我儿", "俺儿", "妻儿",
"拐儿", "聋儿", "乞儿", "患儿", "幼儿", "孤儿", "婴儿", "婴幼儿", "连体儿", "脑瘫儿",
"流浪儿", "体弱儿", "混血儿", "蜜雪儿", "舫儿", "祖儿", "美儿", "应采儿", "可儿", "侄儿",
"孙儿", "侄孙儿", "女儿", "男儿", "红孩儿", "花儿", "虫儿", "马儿", "鸟儿", "猪儿", "猫儿",
"狗儿", "少儿"
}
def _merge_erhua(initials: list[str],
finals: list[str],
word: str,
pos: str) -> list[list[str]]:
"""
Do erhub.
"""
# fix er1
for i, phn in enumerate(finals):
if i == len(finals) - 1 and word[i] == "儿" and phn == 'er1':
finals[i] = 'er2'
# 发音
if word not in must_erhua and (word in not_erhua or
pos in {"a", "j", "nr"}):
return initials, finals
# "……" 等情况直接返回
if len(finals) != len(word):
return initials, finals
assert len(finals) == len(word)
# 与前一个字发同音
new_initials = []
new_finals = []
for i, phn in enumerate(finals):
if i == len(finals) - 1 and word[i] == "儿" and phn in {
"er2", "er5"
} and word[-2:] not in not_erhua and new_finals:
phn = "er" + new_finals[-1][-1]
new_initials.append(initials[i])
new_finals.append(phn)
return new_initials, new_finals
def _g2p(segments):
phones_list = []
word2ph = []
for seg in segments:
pinyins = []
# Replace all English words in the sentence
seg = re.sub("[a-zA-Z]+", "", seg)
seg_cut = psg.lcut(seg)
seg_cut = tone_modifier.pre_merge_for_modify(seg_cut)
initials = []
finals = []
if not is_g2pw:
for word, pos in seg_cut:
if pos == "eng":
continue
sub_initials, sub_finals = _get_initials_finals(word)
sub_finals = tone_modifier.modified_tone(word, pos, sub_finals)
# 儿化
sub_initials, sub_finals = _merge_erhua(sub_initials, sub_finals, word, pos)
initials.append(sub_initials)
finals.append(sub_finals)
# assert len(sub_initials) == len(sub_finals) == len(word)
initials = sum(initials, [])
finals = sum(finals, [])
print("pypinyin结果",initials,finals)
else:
# g2pw采用整句推理
pinyins = g2pw.lazy_pinyin(seg, neutral_tone_with_five=True, style=Style.TONE3)
pre_word_length = 0
for word, pos in seg_cut:
sub_initials = []
sub_finals = []
now_word_length = pre_word_length + len(word)
if pos == 'eng':
pre_word_length = now_word_length
continue
word_pinyins = pinyins[pre_word_length:now_word_length]
# 多音字消歧
word_pinyins = correct_pronunciation(word,word_pinyins)
for pinyin in word_pinyins:
if pinyin[0].isalpha():
sub_initials.append(to_initials(pinyin))
sub_finals.append(to_finals_tone3(pinyin,neutral_tone_with_five=True))
else:
sub_initials.append(pinyin)
sub_finals.append(pinyin)
pre_word_length = now_word_length
sub_finals = tone_modifier.modified_tone(word, pos, sub_finals)
# 儿化
sub_initials, sub_finals = _merge_erhua(sub_initials, sub_finals, word, pos)
initials.append(sub_initials)
finals.append(sub_finals)
initials = sum(initials, [])
finals = sum(finals, [])
# print("g2pw结果",initials,finals)
for c, v in zip(initials, finals):
raw_pinyin = c + v
# NOTE: post process for pypinyin outputs
# we discriminate i, ii and iii
if c == v:
assert c in punctuation
phone = [c]
word2ph.append(1)
else:
v_without_tone = v[:-1]
tone = v[-1]
pinyin = c + v_without_tone
assert tone in "12345"
if c:
# 多音节
v_rep_map = {
"uei": "ui",
"iou": "iu",
"uen": "un",
}
if v_without_tone in v_rep_map.keys():
pinyin = c + v_rep_map[v_without_tone]
else:
# 单音节
pinyin_rep_map = {
"ing": "ying",
"i": "yi",
"in": "yin",
"u": "wu",
}
if pinyin in pinyin_rep_map.keys():
pinyin = pinyin_rep_map[pinyin]
else:
single_rep_map = {
"v": "yu",
"e": "e",
"i": "y",
"u": "w",
}
if pinyin[0] in single_rep_map.keys():
pinyin = single_rep_map[pinyin[0]] + pinyin[1:]
assert pinyin in pinyin_to_symbol_map.keys(), (pinyin, seg, raw_pinyin)
new_c, new_v = pinyin_to_symbol_map[pinyin].split(" ")
new_v = new_v + tone
phone = [new_c, new_v]
word2ph.append(len(phone))
phones_list += phone
return phones_list, word2ph
def replace_punctuation_with_en(text):
text = text.replace("嗯", "恩").replace("呣", "母")
pattern = re.compile("|".join(re.escape(p) for p in rep_map.keys()))
replaced_text = pattern.sub(lambda x: rep_map[x.group()], text)
replaced_text = re.sub(
r"[^\u4e00-\u9fa5A-Za-z" + "".join(punctuation) + r"]+", "", replaced_text
)
return replaced_text
def replace_consecutive_punctuation(text):
punctuations = ''.join(re.escape(p) for p in punctuation)
pattern = f'([{punctuations}])([{punctuations}])+'
result = re.sub(pattern, r'\1', text)
return result
def text_normalize(text):
# https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/paddlespeech/t2s/frontend/zh_normalization
tx = TextNormalizer()
sentences = tx.normalize(text)
dest_text = ""
for sentence in sentences:
dest_text += replace_punctuation(sentence)
# 避免重复标点引起的参考泄露
dest_text = replace_consecutive_punctuation(dest_text)
return dest_text
# 不排除英文的文本格式化
def mix_text_normalize(text):
# https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/paddlespeech/t2s/frontend/zh_normalization
tx = TextNormalizer()
sentences = tx.normalize(text)
dest_text = ""
for sentence in sentences:
dest_text += replace_punctuation_with_en(sentence)
# 避免重复标点引起的参考泄露
dest_text = replace_consecutive_punctuation(dest_text)
return dest_text
if __name__ == "__main__":
text = "啊——但是《原神》是由,米哈\游自主,研发的一款全.新开放世界.冒险游戏"
text = "呣呣呣~就是…大人的鼹鼠党吧?"
text = "你好"
text = text_normalize(text)
print(g2p(text))
# # 示例用法
# text = "这是一个示例文本:,你好!这是一个测试..."
# print(g2p_paddle(text)) # 输出: 这是一个示例文本你好这是一个测试