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import re
import cn2an
from style_bert_vits2.nlp.symbols import PUNCTUATIONS
__REPLACE_MAP = {
"οΌ": ",",
"οΌ": ",",
"οΌ": ",",
"γ": ".",
"οΌ": "!",
"οΌ": "?",
"\n": ".",
"Β·": ",",
"γ": ",",
"...": "β¦",
"$": ".",
"β": "'",
"β": "'",
'"': "'",
"β": "'",
"β": "'",
"οΌ": "'",
"οΌ": "'",
"(": "'",
")": "'",
"γ": "'",
"γ": "'",
"γ": "'",
"γ": "'",
"[": "'",
"]": "'",
"β": "-",
"ο½": "-",
"~": "-",
"γ": "'",
"γ": "'",
}
def normalize_text(text: str) -> str:
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 replace_punctuation(text: str) -> str:
text = text.replace("ε―", "ζ©").replace("ε£", "ζ―")
pattern = re.compile("|".join(re.escape(p) for p in __REPLACE_MAP))
replaced_text = pattern.sub(lambda x: __REPLACE_MAP[x.group()], text)
replaced_text = re.sub(
r"[^\u4e00-\u9fa5" + "".join(PUNCTUATIONS) + r"]+", "", replaced_text
)
return replaced_text
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