63 lines
1.2 KiB
Python
63 lines
1.2 KiB
Python
import re
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import cn2an
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from style_bert_vits2.nlp.symbols import PUNCTUATIONS
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__REPLACE_MAP = {
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"：": ",",
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"；": ",",
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"，": ",",
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"。": ".",
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"！": "!",
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"？": "?",
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"\n": ".",
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"·": ",",
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"、": ",",
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"...": "…",
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"$": ".",
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"“": "'",
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"”": "'",
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'"': "'",
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"‘": "'",
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"’": "'",
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"（": "'",
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"）": "'",
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"(": "'",
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")": "'",
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"《": "'",
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"》": "'",
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"【": "'",
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"】": "'",
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"[": "'",
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"]": "'",
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"—": "-",
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"～": "-",
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"~": "-",
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"「": "'",
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"」": "'",
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}
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def normalize_text(text: str) -> str:
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numbers = re.findall(r"\d+(?:\.?\d+)?", text)
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for number in numbers:
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text = text.replace(number, cn2an.an2cn(number), 1)
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text = replace_punctuation(text)
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return text
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def replace_punctuation(text: str) -> str:
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text = text.replace("嗯", "恩").replace("呣", "母")
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pattern = re.compile("|".join(re.escape(p) for p in __REPLACE_MAP.keys()))
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replaced_text = pattern.sub(lambda x: __REPLACE_MAP[x.group()], text)
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replaced_text = re.sub(
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r"[^\u4e00-\u9fa5" + "".join(PUNCTUATIONS) + r"]+", "", replaced_text
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)
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return replaced_text
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