192 lines
6.1 KiB
Python
192 lines
6.1 KiB
Python
# 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 MyShellTTSBase.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("[⺀-⺙⺛-⻳⼀-⿕々〇〡-〩〸-〺〻㐀-䶵一-鿃豈-鶴侮-頻並-龎]", "", 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 = '하늘' (Unicode : \ud558\ub298), (하 + 늘)
|
|
output = '하늘' (Unicode :\u1112\u1161\u1102\u1173\u11af), (ᄒ + ᅡ + ᄂ + ᅳ + ᆯ)
|
|
|
|
"""
|
|
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)) # '하늘' --> ['ᄒ', 'ᅡ', 'ᄂ', 'ᅳ', 'ᆯ']
|
|
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 = "전 제 일의 가치와 폰타인 대중들이 한 일의 의미를 잘 압니다. 앞으로도 전 제 일에 자부심을 갖고 살아갈 겁니다"
|
|
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('ええ、僕はおきなと申します。こちらの小さいわらべは杏子。ご挨拶が遅れてしまいすみません。あなたの名は?') # Replace with your Chinese text
|
|
|
|
# print(katakana_text) # Output: ニーハオセカイ |