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| # Convert Japanese text to phonemes which is | |
| # compatible with Julius https://github.com/julius-speech/segmentation-kit | |
| import re | |
| import unicodedata | |
| from transformers import AutoTokenizer | |
| from . import punctuation, symbols | |
| from num2words import num2words | |
| from melo.text.ko_dictionary import english_dictionary, etc_dictionary | |
| from anyascii import anyascii | |
| from jamo import hangul_to_jamo | |
| def normalize(text): | |
| text = text.strip() | |
| text = re.sub("[โบ-โบโบ-โปณโผ-โฟใ ใใก-ใฉใธ-ใบใปใ-ไถตไธ-้ฟ่ฑ-้ถดไพฎ-้ ปไธฆ-้พ]", "", text) | |
| text = normalize_with_dictionary(text, etc_dictionary) | |
| text = normalize_english(text) | |
| text = text.lower() | |
| return text | |
| def normalize_with_dictionary(text, dic): | |
| if any(key in text for key in dic.keys()): | |
| pattern = re.compile("|".join(re.escape(key) for key in dic.keys())) | |
| return pattern.sub(lambda x: dic[x.group()], text) | |
| return text | |
| def normalize_english(text): | |
| def fn(m): | |
| word = m.group() | |
| if word in english_dictionary: | |
| return english_dictionary.get(word) | |
| return word | |
| text = re.sub("([A-Za-z]+)", fn, text) | |
| return text | |
| g2p_kr = None | |
| def korean_text_to_phonemes(text, character: str = "hangeul") -> str: | |
| """ | |
| The input and output values look the same, but they are different in Unicode. | |
| example : | |
| input = 'ํ๋' (Unicode : \ud558\ub298), (ํ + ๋) | |
| output = 'แแ กแแ ณแฏ' (Unicode :\u1112\u1161\u1102\u1173\u11af), (แ + แ ก + แ + แ ณ + แฏ) | |
| """ | |
| global g2p_kr # pylint: disable=global-statement | |
| if g2p_kr is None: | |
| from g2pkk import G2p | |
| g2p_kr = G2p() | |
| if character == "english": | |
| from anyascii import anyascii | |
| text = normalize(text) | |
| text = g2p_kr(text) | |
| text = anyascii(text) | |
| return text | |
| text = normalize(text) | |
| text = g2p_kr(text) | |
| text = list(hangul_to_jamo(text)) # 'ํ๋' --> ['แ', 'แ ก', 'แ', 'แ ณ', 'แฏ'] | |
| return "".join(text) | |
| def text_normalize(text): | |
| # res = unicodedata.normalize("NFKC", text) | |
| # res = japanese_convert_numbers_to_words(res) | |
| # # res = "".join([i for i in res if is_japanese_character(i)]) | |
| # res = replace_punctuation(res) | |
| text = normalize(text) | |
| return text | |
| def distribute_phone(n_phone, n_word): | |
| phones_per_word = [0] * n_word | |
| for task in range(n_phone): | |
| min_tasks = min(phones_per_word) | |
| min_index = phones_per_word.index(min_tasks) | |
| phones_per_word[min_index] += 1 | |
| return phones_per_word | |
| # tokenizer = AutoTokenizer.from_pretrained('cl-tohoku/bert-base-japanese-v3') | |
| model_id = 'kykim/bert-kor-base' | |
| tokenizer = AutoTokenizer.from_pretrained(model_id) | |
| def g2p(norm_text): | |
| tokenized = tokenizer.tokenize(norm_text) | |
| phs = [] | |
| ph_groups = [] | |
| for t in tokenized: | |
| if not t.startswith("#"): | |
| ph_groups.append([t]) | |
| else: | |
| ph_groups[-1].append(t.replace("#", "")) | |
| word2ph = [] | |
| for group in ph_groups: | |
| text = "" | |
| for ch in group: | |
| text += ch | |
| if text == '[UNK]': | |
| phs += ['_'] | |
| word2ph += [1] | |
| continue | |
| elif text in punctuation: | |
| phs += [text] | |
| word2ph += [1] | |
| continue | |
| # import pdb; pdb.set_trace() | |
| # phonemes = japanese_text_to_phonemes(text) | |
| # text = g2p_kr(text) | |
| phonemes = korean_text_to_phonemes(text) | |
| # import pdb; pdb.set_trace() | |
| # # phonemes = [i for i in phonemes if i in symbols] | |
| # for i in phonemes: | |
| # assert i in symbols, (group, norm_text, tokenized, i) | |
| phone_len = len(phonemes) | |
| word_len = len(group) | |
| aaa = distribute_phone(phone_len, word_len) | |
| assert len(aaa) == word_len | |
| word2ph += aaa | |
| phs += phonemes | |
| phones = ["_"] + phs + ["_"] | |
| tones = [0 for i in phones] | |
| word2ph = [1] + word2ph + [1] | |
| assert len(word2ph) == len(tokenized) + 2 | |
| return phones, tones, word2ph | |
| def get_bert_feature(text, word2ph, device='cuda'): | |
| from . import japanese_bert | |
| return japanese_bert.get_bert_feature(text, word2ph, device=device, model_id=model_id) | |
| if __name__ == "__main__": | |
| # tokenizer = AutoTokenizer.from_pretrained("./bert/bert-base-japanese-v3") | |
| from text.symbols import symbols | |
| text = "์ ์ ์ผ์ ๊ฐ์น์ ํฐํ์ธ ๋์ค๋ค์ด ํ ์ผ์ ์๋ฏธ๋ฅผ ์ ์๋๋ค. ์์ผ๋ก๋ ์ ์ ์ผ์ ์๋ถ์ฌ์ ๊ฐ๊ณ ์ด์๊ฐ ๊ฒ๋๋ค" | |
| import json | |
| # genshin_data = json.load(open('/data/zwl/workspace/StarRail_Datasets/Index & Scripts/Index/1.3/Korean.json')) | |
| genshin_data = json.load(open('/data/zwl/workspace/Genshin_Datasets/Index & Script/AI Hobbyist Version/Index/4.1/KR_output.json')) | |
| from tqdm import tqdm | |
| new_symbols = [] | |
| for key, item in tqdm(genshin_data.items()): | |
| texts = item.get('voiceContent', '') | |
| if isinstance(texts, list): | |
| texts = ','.join(texts) | |
| if texts is None: | |
| continue | |
| if len(texts) == 0: | |
| continue | |
| text = text_normalize(text) | |
| phones, tones, word2ph = g2p(text) | |
| bert = get_bert_feature(text, word2ph) | |
| import pdb; pdb.set_trace() | |
| for ph in phones: | |
| if ph not in symbols and ph not in new_symbols: | |
| new_symbols.append(ph) | |
| print('update!, now symbols:') | |
| print(new_symbols) | |
| with open('korean_symbol.txt', 'w') as f: | |
| f.write(f'{new_symbols}') | |
| # if __name__ == '__main__': | |
| # from pykakasi import kakasi | |
| # # Initialize kakasi object | |
| # kakasi = kakasi() | |
| # # Set options for converting Chinese characters to Katakana | |
| # kakasi.setMode("J", "H") # Chinese to Katakana | |
| # kakasi.setMode("K", "H") # Hiragana to Katakana | |
| # # Convert Chinese characters to Katakana | |
| # conv = kakasi.getConverter() | |
| # katakana_text = conv.do('ใใใๅใฏใใใชใจ็ณใใพใใใใกใใฎๅฐใใใใในใฏๆๅญใใๆจๆถใ้ ใใฆใใพใใใฟใพใใใใใชใใฎๅใฏ?') # Replace with your Chinese text | |
| # print(katakana_text) # Output: ใใผใใชใปใซใค |