[Add] Implement transliterator and katakana to Hepburn conversion functions

src-python/models/transliterate/transliterate_japanese.py

@@ -0,0 +1,110 @@
+from sudachipy import tokenizer
+from sudachipy import dictionary
+try:
+    from .transliterate_kana_to_hepburn import katakana_to_hepburn
+except ImportError:
+    from transliterate_kana_to_hepburn import katakana_to_hepburn
+
+class Transliterator:
+    def __init__(self):
+        self.tokenizer_obj = dictionary.Dictionary().create()
+        self.mode = tokenizer.Tokenizer.SplitMode.A
+
+    @staticmethod
+    def is_kanji(ch: str) -> bool:
+        return '\u4e00' <= ch <= '\u9fff'
+
+    @staticmethod
+    def kata_to_hira(text: str) -> str:
+        return "".join(
+            chr(ord(c) - 0x60) if 'ァ' <= c <= 'ン' else c
+            for c in text
+        )
+
+    @staticmethod
+    def split_kanji_okurigana(surface: str, reading_kana: str):
+        """
+        1語の表層形(surface)と読み(reading_kana)を
+        [ {"orig":..., "kana":..., "hira":..., "hepburn":...}, ... ] に分割
+        """
+        result = []
+
+        # 表層を「漢字ブロック」と「非漢字ブロック」に分割
+        buf = ""
+        prev_is_kanji = None
+        blocks = []
+        for ch in surface:
+            now_is_kanji = Transliterator.is_kanji(ch)
+            if prev_is_kanji is None or now_is_kanji == prev_is_kanji:
+                buf += ch
+            else:
+                blocks.append((prev_is_kanji, buf))
+                buf = ch
+            prev_is_kanji = now_is_kanji
+        if buf:
+            blocks.append((prev_is_kanji, buf))
+
+        # 読みを分配
+        kana_left = reading_kana
+        for is_kan, part in blocks:
+            if is_kan:
+                # 仮ルール：残りの読みのうち、送り仮名分を除いた前半を充てる
+                # ex. "美しい"(うつくしい): 漢字=美, 残り送り仮名=しい
+                okuri_len = len(blocks[-1][1]) if not blocks[-1][0] else 0
+                kana_for_kan = kana_left[:-okuri_len] if okuri_len else kana_left
+                result.append(
+                    {
+                        "orig": part,
+                        "kana": kana_for_kan,
+                    }
+                )
+                kana_left = kana_left[len(kana_for_kan):]
+            else:
+                # 送り仮名部分 → そのまま残りを割り当てる
+                kana_for_okuri = kana_left
+                result.append(
+                    {
+                        "orig": part,
+                        "kana": kana_for_okuri,
+                    }
+                )
+                kana_left = ""
+
+        return result
+
+    def analyze(self, text: str, use_macron: bool = True):
+        tokens = self.tokenizer_obj.tokenize(text, self.mode)
+
+        results = []
+        for t in tokens:
+            surface = t.surface()
+            parts = self.split_kanji_okurigana(surface, t.reading_form())
+            for p in parts:
+                results.append({
+                    "orig": p["orig"],
+                    "kana": p["kana"],
+                    "hira": self.kata_to_hira(p["kana"]),
+                    "hepburn": katakana_to_hepburn(p["kana"], use_macron=use_macron)
+                })
+        return results
+
+# --- テスト ---
+if __name__ == "__main__":
+    test_cases = [
+        "美しい花を見る",
+        "東京に行く",
+        "漢字とカタカナの混在",
+        "パーティーに行く",
+        "コンピューターを使う",
+        "シェアハウスに住む",
+        "ヴァイオリンを弾く",
+        "ギュウニュウを飲む",
+        "ニューヨークに行く",
+        "ラーメンを食べる",
+        "チョコレートが好き",
+        "SessionIDを取得する",
+    ]
+
+    transliterator = Transliterator()
+    for case in test_cases:
+        print(transliterator.analyze(case))