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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 text import punctuation, symbols
from num2words import num2words
import pyopenjtalk
import jaconv
def kata2phoneme(text: str) -> str:
"""Convert katakana text to phonemes."""
text = text.strip()
if text == "ー":
return ["ー"]
elif text.startswith("ー"):
return ["ー"] + kata2phoneme(text[1:])
res = []
prev = None
while text:
if re.match(_MARKS, text):
res.append(text)
text = text[1:]
continue
if text.startswith("ー"):
if prev:
res.append(prev[-1])
text = text[1:]
continue
res += pyopenjtalk.g2p(text).lower().replace("cl", "q").split(" ")
break
# res = _COLON_RX.sub(":", res)
return res
def hira2kata(text: str) -> str:
return jaconv.hira2kata(text)
_SYMBOL_TOKENS = set(list("・、。?!"))
_NO_YOMI_TOKENS = set(list("「」『』―()[][]"))
_MARKS = re.compile(
r"[^A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]"
)
def text2kata(text: str) -> str:
parsed = pyopenjtalk.run_frontend(text)
res = []
for parts in parsed:
word, yomi = replace_punctuation(parts["string"]), parts["pron"].replace(
"’", ""
)
if yomi:
if re.match(_MARKS, yomi):
if len(word) > 1:
word = [replace_punctuation(i) for i in list(word)]
yomi = word
res += yomi
sep += word
continue
elif word not in rep_map.keys() and word not in rep_map.values():
word = ","
yomi = word
res.append(yomi)
else:
if word in _SYMBOL_TOKENS:
res.append(word)
elif word in ("っ", "ッ"):
res.append("ッ")
elif word in _NO_YOMI_TOKENS:
pass
else:
res.append(word)
return hira2kata("".join(res))
def text2sep_kata(text: str) -> (list, list):
parsed = pyopenjtalk.run_frontend(text)
res = []
sep = []
for parts in parsed:
word, yomi = replace_punctuation(parts["string"]), parts["pron"].replace(
"’", ""
)
if yomi:
if re.match(_MARKS, yomi):
if len(word) > 1:
word = [replace_punctuation(i) for i in list(word)]
yomi = word
res += yomi
sep += word
continue
elif word not in rep_map.keys() and word not in rep_map.values():
word = ","
yomi = word
res.append(yomi)
else:
if word in _SYMBOL_TOKENS:
res.append(word)
elif word in ("っ", "ッ"):
res.append("ッ")
elif word in _NO_YOMI_TOKENS:
pass
else:
res.append(word)
sep.append(word)
return sep, [hira2kata(i) for i in res], get_accent(parsed)
def get_accent(parsed):
labels = pyopenjtalk.make_label(parsed)
phonemes = []
accents = []
for n, label in enumerate(labels):
phoneme = re.search(r"\-([^\+]*)\+", label).group(1)
if phoneme not in ["sil", "pau"]:
phonemes.append(phoneme.replace("cl", "q").lower())
else:
continue
a1 = int(re.search(r"/A:(\-?[0-9]+)\+", label).group(1))
a2 = int(re.search(r"\+(\d+)\+", label).group(1))
if re.search(r"\-([^\+]*)\+", labels[n + 1]).group(1) in ["sil", "pau"]:
a2_next = -1
else:
a2_next = int(re.search(r"\+(\d+)\+", labels[n + 1]).group(1))
# Falling
if a1 == 0 and a2_next == a2 + 1:
accents.append(-1)
# Rising
elif a2 == 1 and a2_next == 2:
accents.append(1)
else:
accents.append(0)
return list(zip(phonemes, accents))
_ALPHASYMBOL_YOMI = {
"#": "シャープ",
"%": "パーセント",
"&": "アンド",
"+": "プラス",
"-": "マイナス",
":": "コロン",
";": "セミコロン",
"<": "小なり",
"=": "イコール",
">": "大なり",
"@": "アット",
"a": "エー",
"b": "ビー",
"c": "シー",
"d": "ディー",
"e": "イー",
"f": "エフ",
"g": "ジー",
"h": "エイチ",
"i": "アイ",
"j": "ジェー",
"k": "ケー",
"l": "エル",
"m": "エム",
"n": "エヌ",
"o": "オー",
"p": "ピー",
"q": "キュー",
"r": "アール",
"s": "エス",
"t": "ティー",
"u": "ユー",
"v": "ブイ",
"w": "ダブリュー",
"x": "エックス",
"y": "ワイ",
"z": "ゼット",
"α": "アルファ",
"β": "ベータ",
"γ": "ガンマ",
"δ": "デルタ",
"ε": "イプシロン",
"ζ": "ゼータ",
"η": "イータ",
"θ": "シータ",
"ι": "イオタ",
"κ": "カッパ",
"λ": "ラムダ",
"μ": "ミュー",
"ν": "ニュー",
"ξ": "クサイ",
"ο": "オミクロン",
"π": "パイ",
"ρ": "ロー",
"σ": "シグマ",
"τ": "タウ",
"υ": "ウプシロン",
"φ": "ファイ",
"χ": "カイ",
"ψ": "プサイ",
"ω": "オメガ",
}
_NUMBER_WITH_SEPARATOR_RX = re.compile("[0-9]{1,3}(,[0-9]{3})+")
_CURRENCY_MAP = {"$": "ドル", "¥": "円", "£": "ポンド", "€": "ユーロ"}
_CURRENCY_RX = re.compile(r"([$¥£€])([0-9.]*[0-9])")
_NUMBER_RX = re.compile(r"[0-9]+(\.[0-9]+)?")
def japanese_convert_numbers_to_words(text: str) -> str:
res = _NUMBER_WITH_SEPARATOR_RX.sub(lambda m: m[0].replace(",", ""), text)
res = _CURRENCY_RX.sub(lambda m: m[2] + _CURRENCY_MAP.get(m[1], m[1]), res)
res = _NUMBER_RX.sub(lambda m: num2words(m[0], lang="ja"), res)
return res
def japanese_convert_alpha_symbols_to_words(text: str) -> str:
return "".join([_ALPHASYMBOL_YOMI.get(ch, ch) for ch in text.lower()])
def japanese_text_to_phonemes(text: str) -> str:
"""Convert Japanese text to phonemes."""
res = unicodedata.normalize("NFKC", text)
res = japanese_convert_numbers_to_words(res)
# res = japanese_convert_alpha_symbols_to_words(res)
res = text2kata(res)
res = kata2phoneme(res)
return res
def is_japanese_character(char):
# 定义日语文字系统的 Unicode 范围
japanese_ranges = [
(0x3040, 0x309F), # 平假名
(0x30A0, 0x30FF), # 片假名
(0x4E00, 0x9FFF), # 汉字 (CJK Unified Ideographs)
(0x3400, 0x4DBF), # 汉字扩展 A
(0x20000, 0x2A6DF), # 汉字扩展 B
# 可以根据需要添加其他汉字扩展范围
]
# 将字符的 Unicode 编码转换为整数
char_code = ord(char)
# 检查字符是否在任何一个日语范围内
for start, end in japanese_ranges:
if start <= char_code <= end:
return True
return False
rep_map = {
":": ",",
";": ",",
",": ",",
"。": ".",
"!": "!",
"?": "?",
"\n": ".",
".": ".",
"…": "...",
"···": "...",
"・・・": "...",
"·": ",",
"・": ",",
"、": ",",
"$": ".",
"“": "'",
"”": "'",
'"': "'",
"‘": "'",
"’": "'",
"(": "'",
")": "'",
"(": "'",
")": "'",
"《": "'",
"》": "'",
"【": "'",
"】": "'",
"[": "'",
"]": "'",
"—": "-",
"−": "-",
"~": "-",
"~": "-",
"「": "'",
"」": "'",
}
def replace_punctuation(text):
pattern = re.compile("|".join(re.escape(p) for p in rep_map.keys()))
replaced_text = pattern.sub(lambda x: rep_map[x.group()], text)
replaced_text = re.sub(
r"[^\u3040-\u309F\u30A0-\u30FF\u4E00-\u9FFF\u3400-\u4DBF\u3005"
+ "".join(punctuation)
+ r"]+",
"",
replaced_text,
)
return replaced_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)
res = res.replace("゙", "")
return res
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
def handle_long(sep_phonemes):
for i in range(len(sep_phonemes)):
if sep_phonemes[i][0] == "ー":
sep_phonemes[i][0] = sep_phonemes[i - 1][-1]
if "ー" in sep_phonemes[i]:
for j in range(len(sep_phonemes[i])):
if sep_phonemes[i][j] == "ー":
sep_phonemes[i][j] = sep_phonemes[i][j - 1][-1]
return sep_phonemes
tokenizer = AutoTokenizer.from_pretrained("./bert/deberta-v2-large-japanese-char-wwm")
def align_tones(phones, tones):
res = []
for pho in phones:
temp = [0] * len(pho)
for idx, p in enumerate(pho):
if len(tones) == 0:
break
if p == tones[0][0]:
temp[idx] = tones[0][1]
if idx > 0:
temp[idx] += temp[idx - 1]
tones.pop(0)
temp = [0] + temp
temp = temp[:-1]
if -1 in temp:
temp = [i + 1 for i in temp]
res.append(temp)
res = [i for j in res for i in j]
assert not any([i < 0 for i in res]) and not any([i > 1 for i in res])
return res
def rearrange_tones(tones, phones):
res = [0] * len(tones)
for i in range(len(tones)):
if i == 0:
if tones[i] not in punctuation:
res[i] = 1
elif tones[i] == prev:
if phones[i] in punctuation:
res[i] = 0
else:
res[i] = 1
elif tones[i] > prev:
res[i] = 2
elif tones[i] < prev:
res[i - 1] = 3
res[i] = 1
prev = tones[i]
return res
def g2p(norm_text):
sep_text, sep_kata, acc = text2sep_kata(norm_text)
sep_tokenized = []
for i in sep_text:
if i not in punctuation:
sep_tokenized.append(tokenizer.tokenize(i))
else:
sep_tokenized.append([i])
sep_phonemes = handle_long([kata2phoneme(i) for i in sep_kata])
# 异常处理,MeCab不认识的词的话会一路传到这里来,然后炸掉。目前来看只有那些超级稀有的生僻词会出现这种情况
for i in sep_phonemes:
for j in i:
assert j in symbols, (sep_text, sep_kata, sep_phonemes)
tones = align_tones(sep_phonemes, acc)
word2ph = []
for token, phoneme in zip(sep_tokenized, sep_phonemes):
phone_len = len(phoneme)
word_len = len(token)
aaa = distribute_phone(phone_len, word_len)
word2ph += aaa
phones = ["_"] + [j for i in sep_phonemes for j in i] + ["_"]
# tones = [0] + rearrange_tones(tones, phones[1:-1]) + [0]
tones = [0] + tones + [0]
word2ph = [1] + word2ph + [1]
assert len(phones) == len(tones)
return phones, tones, word2ph
if __name__ == "__main__":
tokenizer = AutoTokenizer.from_pretrained("./bert/deberta-v2-large-japanese")
text = "hello,こんにちは、世界ー!……"
from text.japanese_bert import get_bert_feature
text = text_normalize(text)
print(text)
phones, tones, word2ph = g2p(text)
bert = get_bert_feature(text, word2ph)
print(phones, tones, word2ph, bert.shape)