MeloTTS / melo /text /chinese_mix.py
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import os
import re
import cn2an
from pypinyin import lazy_pinyin, Style
# from text.symbols import punctuation
from .symbols import language_tone_start_map
from .tone_sandhi import ToneSandhi
from .english import g2p as g2p_en
from transformers import AutoTokenizer
punctuation = ["!", "?", "…", ",", ".", "'", "-"]
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.posseg as psg
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_a-zA-Z\s" + "".join(punctuation) + r"]+", "", replaced_text)
replaced_text = re.sub(r"[\s]+", " ", replaced_text)
return replaced_text
def g2p(text, impl='v2'):
pattern = r"(?<=[{0}])\s*".format("".join(punctuation))
sentences = [i for i in re.split(pattern, text) if i.strip() != ""]
if impl == 'v1':
_func = _g2p
elif impl == 'v2':
_func = _g2p_v2
else:
raise NotImplementedError()
phones, tones, word2ph = _func(sentences)
assert sum(word2ph) == len(phones)
# assert len(word2ph) == len(text) # Sometimes it will crash,you can add a try-catch.
phones = ["_"] + phones + ["_"]
tones = [0] + tones + [0]
word2ph = [1] + word2ph + [1]
return phones, tones, 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
model_id = 'bert-base-multilingual-uncased'
tokenizer = AutoTokenizer.from_pretrained(model_id)
def _g2p(segments):
phones_list = []
tones_list = []
word2ph = []
for seg in segments:
# Replace all English words in the sentence
# seg = re.sub("[a-zA-Z]+", "", seg)
seg_cut = psg.lcut(seg)
initials = []
finals = []
seg_cut = tone_modifier.pre_merge_for_modify(seg_cut)
for word, pos in seg_cut:
if pos == "eng":
initials.append(['EN_WORD'])
finals.append([word])
else:
sub_initials, sub_finals = _get_initials_finals(word)
sub_finals = tone_modifier.modified_tone(word, pos, sub_finals)
initials.append(sub_initials)
finals.append(sub_finals)
# assert len(sub_initials) == len(sub_finals) == len(word)
initials = sum(initials, [])
finals = sum(finals, [])
#
for c, v in zip(initials, finals):
if c == 'EN_WORD':
tokenized_en = tokenizer.tokenize(v)
phones_en, tones_en, word2ph_en = g2p_en(text=None, pad_start_end=False, tokenized=tokenized_en)
# apply offset to tones_en
tones_en = [t + language_tone_start_map['EN'] for t in tones_en]
phones_list += phones_en
tones_list += tones_en
word2ph += word2ph_en
else:
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]
tone = "0"
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)
phone = pinyin_to_symbol_map[pinyin].split(" ")
word2ph.append(len(phone))
phones_list += phone
tones_list += [int(tone)] * len(phone)
return phones_list, tones_list, word2ph
def text_normalize(text):
numbers = re.findall(r"\d+(?:\.?\d+)?", text)
for number in numbers:
text = text.replace(number, cn2an.an2cn(number), 1)
text = replace_punctuation(text)
return text
def get_bert_feature(text, word2ph, device):
from . import chinese_bert
return chinese_bert.get_bert_feature(text, word2ph, model_id='bert-base-multilingual-uncased', device=device)
from .chinese import _g2p as _chinese_g2p
def _g2p_v2(segments):
spliter = '#$&^!@'
phones_list = []
tones_list = []
word2ph = []
for text in segments:
assert spliter not in text
# replace all english words
text = re.sub('([a-zA-Z\s]+)', lambda x: f'{spliter}{x.group(1)}{spliter}', text)
texts = text.split(spliter)
texts = [t for t in texts if len(t) > 0]
for text in texts:
if re.match('[a-zA-Z\s]+', text):
# english
tokenized_en = tokenizer.tokenize(text)
phones_en, tones_en, word2ph_en = g2p_en(text=None, pad_start_end=False, tokenized=tokenized_en)
# apply offset to tones_en
tones_en = [t + language_tone_start_map['EN'] for t in tones_en]
phones_list += phones_en
tones_list += tones_en
word2ph += word2ph_en
else:
phones_zh, tones_zh, word2ph_zh = _chinese_g2p([text])
phones_list += phones_zh
tones_list += tones_zh
word2ph += word2ph_zh
return phones_list, tones_list, word2ph
if __name__ == "__main__":
# from text.chinese_bert import get_bert_feature
text = "NFT啊!chemistry 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 = '我最近在学习machine learning,希望能够在未来的artificial intelligence领域有所建树。'
text = '今天下午,我们准备去shopping mall购物,然后晚上去看一场movie。'
text = '我们现在 also 能够 help 很多公司 use some machine learning 的 algorithms 啊!'
text = text_normalize(text)
print(text)
phones, tones, word2ph = g2p(text, impl='v2')
bert = get_bert_feature(text, word2ph, device='cuda:0')
print(phones)
import pdb; pdb.set_trace()
# # 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