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* sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * bugfix * update with main (#1631) * update seaco finetune * v1.0.24 --------- Co-authored-by: 维石 <shixian.shi@alibaba-inc.com> * sensevoice * sensevoice * sensevoice * update with main (#1638) * update seaco finetune * v1.0.24 * update rwkv template --------- Co-authored-by: 维石 <shixian.shi@alibaba-inc.com> * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * whisper * whisper * update style * update style --------- Co-authored-by: 维石 <shixian.shi@alibaba-inc.com>
75 lines
1.9 KiB
Python
75 lines
1.9 KiB
Python
# Referenced from https://github.com/hccho2/Tacotron-Wavenet-Vocoder-Korean
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import re
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class KoreanCleaner:
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@classmethod
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def _normalize_numbers(cls, text):
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number_to_kor = {
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"0": "영",
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"1": "일",
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"2": "이",
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"3": "삼",
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"4": "사",
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"5": "오",
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"6": "육",
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"7": "칠",
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"8": "팔",
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"9": "구",
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}
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new_text = "".join(
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number_to_kor[char] if char in number_to_kor.keys() else char for char in text
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)
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return new_text
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@classmethod
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def _normalize_english_text(cls, text):
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upper_alphabet_to_kor = {
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"A": "에이",
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"B": "비",
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"C": "씨",
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"D": "디",
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"E": "이",
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"F": "에프",
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"G": "지",
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"H": "에이치",
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"I": "아이",
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"J": "제이",
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"K": "케이",
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"L": "엘",
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"M": "엠",
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"N": "엔",
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"O": "오",
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"P": "피",
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"Q": "큐",
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"R": "알",
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"S": "에스",
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"T": "티",
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"U": "유",
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"V": "브이",
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"W": "더블유",
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"X": "엑스",
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"Y": "와이",
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"Z": "지",
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}
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new_text = re.sub("[a-z]+", lambda x: str.upper(x.group()), text)
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new_text = "".join(
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upper_alphabet_to_kor[char] if char in upper_alphabet_to_kor.keys() else char
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for char in new_text
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)
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return new_text
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@classmethod
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def normalize_text(cls, text):
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# stage 0 : text strip
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text = text.strip()
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# stage 1 : normalize numbers
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text = cls._normalize_numbers(text)
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# stage 2 : normalize english text
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text = cls._normalize_english_text(text)
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return text
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