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import re |
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import unicodedata |
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from transformers import AutoTokenizer |
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from text import punctuation, symbols |
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from num2words import num2words |
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import pyopenjtalk |
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import jaconv |
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def kata2phoneme(text: str) -> str: |
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"""Convert katakana text to phonemes.""" |
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text = text.strip() |
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if text == "ー": |
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return ["ー"] |
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elif text.startswith("ー"): |
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return ["ー"] + kata2phoneme(text[1:]) |
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res = [] |
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prev = None |
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while text: |
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if re.match(_MARKS, text): |
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res.append(text) |
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text = text[1:] |
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continue |
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if text.startswith("ー"): |
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if prev: |
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res.append(prev[-1]) |
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text = text[1:] |
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continue |
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res += pyopenjtalk.g2p(text).lower().replace("cl", "q").split(" ") |
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break |
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return res |
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def hira2kata(text: str) -> str: |
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return jaconv.hira2kata(text) |
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_SYMBOL_TOKENS = set(list("・、。?!")) |
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_NO_YOMI_TOKENS = set(list("「」『』―()[][]")) |
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_MARKS = re.compile( |
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r"[^A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]" |
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) |
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def text2kata(text: str) -> str: |
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parsed = pyopenjtalk.run_frontend(text) |
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res = [] |
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for parts in parsed: |
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word, yomi = replace_punctuation(parts["string"]), parts["pron"].replace( |
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"’", "" |
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) |
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if yomi: |
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if re.match(_MARKS, yomi): |
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if len(word) > 1: |
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word = [replace_punctuation(i) for i in list(word)] |
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yomi = word |
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res += yomi |
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sep += word |
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continue |
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elif word not in rep_map.keys() and word not in rep_map.values(): |
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word = "," |
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yomi = word |
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res.append(yomi) |
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else: |
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if word in _SYMBOL_TOKENS: |
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res.append(word) |
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elif word in ("っ", "ッ"): |
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res.append("ッ") |
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elif word in _NO_YOMI_TOKENS: |
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pass |
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else: |
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res.append(word) |
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return hira2kata("".join(res)) |
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def text2sep_kata(text: str) -> (list, list): |
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parsed = pyopenjtalk.run_frontend(text) |
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res = [] |
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sep = [] |
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for parts in parsed: |
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word, yomi = replace_punctuation(parts["string"]), parts["pron"].replace( |
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"’", "" |
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) |
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if yomi: |
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if re.match(_MARKS, yomi): |
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if len(word) > 1: |
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word = [replace_punctuation(i) for i in list(word)] |
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yomi = word |
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res += yomi |
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sep += word |
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continue |
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elif word not in rep_map.keys() and word not in rep_map.values(): |
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word = "," |
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yomi = word |
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res.append(yomi) |
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else: |
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if word in _SYMBOL_TOKENS: |
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res.append(word) |
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elif word in ("っ", "ッ"): |
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res.append("ッ") |
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elif word in _NO_YOMI_TOKENS: |
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pass |
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else: |
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res.append(word) |
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sep.append(word) |
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return sep, [hira2kata(i) for i in res], get_accent(parsed) |
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def get_accent(parsed): |
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labels = pyopenjtalk.make_label(parsed) |
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phonemes = [] |
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accents = [] |
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for n, label in enumerate(labels): |
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phoneme = re.search(r"\-([^\+]*)\+", label).group(1) |
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if phoneme not in ["sil", "pau"]: |
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phonemes.append(phoneme.replace("cl", "q").lower()) |
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else: |
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continue |
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a1 = int(re.search(r"/A:(\-?[0-9]+)\+", label).group(1)) |
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a2 = int(re.search(r"\+(\d+)\+", label).group(1)) |
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if re.search(r"\-([^\+]*)\+", labels[n + 1]).group(1) in ["sil", "pau"]: |
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a2_next = -1 |
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else: |
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a2_next = int(re.search(r"\+(\d+)\+", labels[n + 1]).group(1)) |
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if a1 == 0 and a2_next == a2 + 1: |
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accents.append(-1) |
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elif a2 == 1 and a2_next == 2: |
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accents.append(1) |
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else: |
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accents.append(0) |
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return list(zip(phonemes, accents)) |
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_ALPHASYMBOL_YOMI = { |
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"#": "シャープ", |
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"%": "パーセント", |
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"&": "アンド", |
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"+": "プラス", |
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"-": "マイナス", |
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":": "コロン", |
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";": "セミコロン", |
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"<": "小なり", |
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"=": "イコール", |
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">": "大なり", |
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"@": "アット", |
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"a": "エー", |
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"b": "ビー", |
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"c": "シー", |
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"d": "ディー", |
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"e": "イー", |
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"f": "エフ", |
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"g": "ジー", |
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"h": "エイチ", |
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"i": "アイ", |
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"j": "ジェー", |
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"k": "ケー", |
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"l": "エル", |
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"m": "エム", |
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"n": "エヌ", |
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"o": "オー", |
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"p": "ピー", |
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"q": "キュー", |
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"r": "アール", |
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"s": "エス", |
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"t": "ティー", |
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"u": "ユー", |
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"v": "ブイ", |
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"w": "ダブリュー", |
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"x": "エックス", |
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"y": "ワイ", |
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"z": "ゼット", |
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"α": "アルファ", |
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"β": "ベータ", |
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"γ": "ガンマ", |
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"δ": "デルタ", |
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"ε": "イプシロン", |
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"ζ": "ゼータ", |
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"η": "イータ", |
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"θ": "シータ", |
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"ι": "イオタ", |
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"κ": "カッパ", |
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"λ": "ラムダ", |
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"μ": "ミュー", |
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"ν": "ニュー", |
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"ξ": "クサイ", |
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"ο": "オミクロン", |
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"π": "パイ", |
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"ρ": "ロー", |
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"σ": "シグマ", |
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"τ": "タウ", |
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"υ": "ウプシロン", |
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"φ": "ファイ", |
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"χ": "カイ", |
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"ψ": "プサイ", |
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"ω": "オメガ", |
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} |
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_NUMBER_WITH_SEPARATOR_RX = re.compile("[0-9]{1,3}(,[0-9]{3})+") |
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_CURRENCY_MAP = {"$": "ドル", "¥": "円", "£": "ポンド", "€": "ユーロ"} |
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_CURRENCY_RX = re.compile(r"([$¥£€])([0-9.]*[0-9])") |
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_NUMBER_RX = re.compile(r"[0-9]+(\.[0-9]+)?") |
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def japanese_convert_numbers_to_words(text: str) -> str: |
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res = _NUMBER_WITH_SEPARATOR_RX.sub(lambda m: m[0].replace(",", ""), text) |
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res = _CURRENCY_RX.sub(lambda m: m[2] + _CURRENCY_MAP.get(m[1], m[1]), res) |
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res = _NUMBER_RX.sub(lambda m: num2words(m[0], lang="ja"), res) |
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return res |
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def japanese_convert_alpha_symbols_to_words(text: str) -> str: |
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return "".join([_ALPHASYMBOL_YOMI.get(ch, ch) for ch in text.lower()]) |
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def japanese_text_to_phonemes(text: str) -> str: |
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"""Convert Japanese text to phonemes.""" |
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res = unicodedata.normalize("NFKC", text) |
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res = japanese_convert_numbers_to_words(res) |
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res = text2kata(res) |
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res = kata2phoneme(res) |
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return res |
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def is_japanese_character(char): |
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japanese_ranges = [ |
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(0x3040, 0x309F), |
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(0x30A0, 0x30FF), |
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(0x4E00, 0x9FFF), |
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(0x3400, 0x4DBF), |
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(0x20000, 0x2A6DF), |
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] |
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char_code = ord(char) |
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for start, end in japanese_ranges: |
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if start <= char_code <= end: |
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return True |
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return False |
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rep_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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"~": "-", |
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"~": "-", |
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"「": "'", |
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"」": "'", |
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} |
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def replace_punctuation(text): |
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pattern = re.compile("|".join(re.escape(p) for p in rep_map.keys())) |
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replaced_text = pattern.sub(lambda x: rep_map[x.group()], text) |
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replaced_text = re.sub( |
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r"[^\u3040-\u309F\u30A0-\u30FF\u4E00-\u9FFF\u3400-\u4DBF\u3005" |
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+ "".join(punctuation) |
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+ r"]+", |
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"", |
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replaced_text, |
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) |
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return replaced_text |
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def text_normalize(text): |
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res = unicodedata.normalize("NFKC", text) |
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res = japanese_convert_numbers_to_words(res) |
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res = replace_punctuation(res) |
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res = res.replace("゙", "") |
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return res |
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def distribute_phone(n_phone, n_word): |
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phones_per_word = [0] * n_word |
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for task in range(n_phone): |
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min_tasks = min(phones_per_word) |
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min_index = phones_per_word.index(min_tasks) |
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phones_per_word[min_index] += 1 |
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return phones_per_word |
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def handle_long(sep_phonemes): |
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for i in range(len(sep_phonemes)): |
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if sep_phonemes[i][0] == "ー": |
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sep_phonemes[i][0] = sep_phonemes[i - 1][-1] |
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if "ー" in sep_phonemes[i]: |
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for j in range(len(sep_phonemes[i])): |
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if sep_phonemes[i][j] == "ー": |
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sep_phonemes[i][j] = sep_phonemes[i][j - 1][-1] |
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return sep_phonemes |
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tokenizer = AutoTokenizer.from_pretrained("./bert/deberta-v2-large-japanese-char-wwm") |
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def align_tones(phones, tones): |
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res = [] |
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for pho in phones: |
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temp = [0] * len(pho) |
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for idx, p in enumerate(pho): |
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if len(tones) == 0: |
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break |
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if p == tones[0][0]: |
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temp[idx] = tones[0][1] |
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if idx > 0: |
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temp[idx] += temp[idx - 1] |
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tones.pop(0) |
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temp = [0] + temp |
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temp = temp[:-1] |
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if -1 in temp: |
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temp = [i + 1 for i in temp] |
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res.append(temp) |
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res = [i for j in res for i in j] |
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assert not any([i < 0 for i in res]) and not any([i > 1 for i in res]) |
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return res |
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def rearrange_tones(tones, phones): |
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res = [0] * len(tones) |
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for i in range(len(tones)): |
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if i == 0: |
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if tones[i] not in punctuation: |
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res[i] = 1 |
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elif tones[i] == prev: |
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if phones[i] in punctuation: |
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res[i] = 0 |
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else: |
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res[i] = 1 |
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elif tones[i] > prev: |
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res[i] = 2 |
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elif tones[i] < prev: |
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res[i - 1] = 3 |
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res[i] = 1 |
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prev = tones[i] |
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return res |
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def g2p(norm_text): |
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sep_text, sep_kata, acc = text2sep_kata(norm_text) |
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sep_tokenized = [] |
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for i in sep_text: |
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if i not in punctuation: |
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sep_tokenized.append(tokenizer.tokenize(i)) |
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else: |
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sep_tokenized.append([i]) |
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sep_phonemes = handle_long([kata2phoneme(i) for i in sep_kata]) |
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for i in sep_phonemes: |
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for j in i: |
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assert j in symbols, (sep_text, sep_kata, sep_phonemes) |
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tones = align_tones(sep_phonemes, acc) |
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word2ph = [] |
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for token, phoneme in zip(sep_tokenized, sep_phonemes): |
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phone_len = len(phoneme) |
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word_len = len(token) |
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aaa = distribute_phone(phone_len, word_len) |
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word2ph += aaa |
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phones = ["_"] + [j for i in sep_phonemes for j in i] + ["_"] |
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tones = [0] + tones + [0] |
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word2ph = [1] + word2ph + [1] |
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assert len(phones) == len(tones) |
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return phones, tones, word2ph |
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if __name__ == "__main__": |
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tokenizer = AutoTokenizer.from_pretrained("./bert/deberta-v2-large-japanese") |
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text = "hello,こんにちは、世界ー!……" |
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from text.japanese_bert import get_bert_feature |
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text = text_normalize(text) |
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print(text) |
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phones, tones, word2ph = g2p(text) |
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bert = get_bert_feature(text, word2ph) |
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print(phones, tones, word2ph, bert.shape) |
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