diff --git a/.gitattributes b/.gitattributes
index a6344aac8c09253b3b630fb776ae94478aa0275b..a0640d14a76658aabe9b9d11333f7f9913069004 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.opus filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text
+*.ogg filter=lfs diff=lfs merge=lfs -text
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..21d0b898ff61470da684cc5e8f7d6efa648de8cf
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1 @@
+.venv/
diff --git a/README.md b/README.md
index 408d21ce23bf1bab6ef1083c4da9ec1b14e3d781..69ea1e9a52baef573b5ee9f3d7939270f248666b 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
 ---
-title: Nijivoice Voice Actors
-emoji: 🏆
+title: にじボイスのキャラと声優さんの対応表デモ
+emoji: 🤔
 colorFrom: yellow
 colorTo: pink
 sdk: gradio
diff --git a/app.py b/app.py
new file mode 100644
index 0000000000000000000000000000000000000000..1951979d552a01f678a2dc696e3ec16c83624672
--- /dev/null
+++ b/app.py
@@ -0,0 +1,224 @@
+# player.py
+from __future__ import annotations
+
+from pathlib import Path
+from typing import List, Optional
+
+import gradio as gr
+import pandas as pd
+
+DATA_CSV = Path("data.csv")
+SAMPLES_ROOT = Path("./samples")
+AUDIO_EXTS = (".opus",)
+
+# 表示ヘッダー（Dataframe の headers と完全一致にする）
+HEADERS = ["にじボイスでのキャラ名", "声優名", "自信"]  # speaker_name / va / prob
+
+
+# ─── 便利関数 ───
+def load_csv(csv_path: Path) -> pd.DataFrame:
+    df = pd.read_csv(csv_path, dtype=str, keep_default_na=False)
+    need_cols = ["speaker_name", "staff_id"]  # va / prob は無くても OK
+    for c in need_cols:
+        if c not in df.columns:
+            raise ValueError(f"CSV に必須列 '{c}' がありません。")
+    return df.fillna("")
+
+
+def tts_path_for(speaker: str, idx: int) -> Optional[Path]:
+    p = SAMPLES_ROOT / speaker / "tts" / f"{idx}.opus"
+    return p if p.exists() else None
+
+
+def guess_numbers_for(speaker: str) -> List[str]:
+    gdir = SAMPLES_ROOT / speaker / "guess"
+    if not gdir.exists():
+        return []
+    nums = set()
+    for ext in AUDIO_EXTS:
+        for p in gdir.glob(f"*{ext}"):
+            stem = p.stem
+            if stem.isdigit():
+                nums.add(int(stem))
+    return [str(n) for n in sorted(nums)]
+
+
+def guess_path_for(speaker: str, num: str) -> Optional[Path]:
+    gdir = SAMPLES_ROOT / speaker / "guess"
+    for ext in AUDIO_EXTS:
+        p = gdir / f"{num}{ext}"
+        if p.exists():
+            return p
+    return None
+
+
+def filter_df(df: pd.DataFrame, q: str) -> pd.DataFrame:
+    if not q:
+        return df
+    mask = df["speaker_name"].str.contains(q, case=False, na=False)
+    return df[mask]
+
+
+def build_vndb_markdown(staff_id: str, va: str) -> str:
+    sid = (staff_id or "").strip()
+    va_ = (va or "").strip()
+    parts = ["## 予想声優"]
+    if va_ and not sid:
+        parts.append(f"**{va_}**")
+    elif va_ and sid:
+        parts.append(f"**[{va_}](https://vndb.org/{sid})**")
+    return "  \n".join(parts)
+
+
+# 表示用 DF に変換（日本語 3 列で揃える）
+def to_display_df(df: pd.DataFrame) -> pd.DataFrame:
+    work = df.copy()
+    if "va" not in work.columns:
+        work["va"] = ""
+    if "prob" not in work.columns:
+        work["prob"] = ""
+    disp = work[["speaker_name", "va", "prob"]]
+    disp.columns = HEADERS
+    return disp
+
+
+def on_tts_pick(speaker: str, idx: int | str):
+    try:
+        i = int(idx)
+    except Exception:
+        return None
+    p = tts_path_for(speaker, i)
+    return p if p else None
+
+
+def on_guess_pick(speaker: str, num: str | int):
+    if num is None or num == "":
+        return None
+    p = guess_path_for(speaker, str(num))
+    return p if p else None
+
+
+md = """
+# にじボイスの声優予想
+
+[にじボイス](https://nijivoice.com/) のキャラクター音声の声優をAIで予想しました。その結果を一覧表示し、音声を再生できるアプリです。
+
+## 使い方
+
+1. 表からキャラクター名を選択します
+2. 左側に、にじボイスでの音声例が3つ表示されます
+3. 右側に、予想された声優名が表示され、似た声の音声例をいくつか再生できます
+4. 表の右上の検索ボックスで検索もできます
+
+## 注意
+
+- この結果は、あくまで音声が似ている声優を機械的に予想したものであり、にじボイスがこれらの声優のデータを用いて学習しているか、または学習時に声優さんの許可を得ているかを示すものではありません
+- 特に自信度が1.0より低い場合で、あまり似ていない場合や、より似ている声優さんがいる場合もあります
+- なお、リンク先の声優情報内では複数の名義が掲載されている場合がありますが、これは何故か声がすごく似ているだけであって、同一人物であると主張するものではありません。
+"""
+
+
+# ─── UI 構築 ───
+def build_demo(csv_path: Path):
+    # 1) 元 CSV 読み込み
+    df = load_csv(csv_path)
+
+    # 2) クリック時に参照するメタ辞書（speaker_name は一意想定）
+    meta_by_speaker = {
+        str(row.get("speaker_name", "")).strip(): {
+            "staff_id": str(row.get("staff_id", "") or "").strip(),
+            "va": str(row.get("va", "") or "").strip(),
+            "prob": str(row.get("prob", "") or "").strip(),
+        }
+        for _, row in df.iterrows()
+        if str(row.get("speaker_name", "")).strip()
+    }
+
+    # 3) 表示用 DF（日本語 3 列）
+    display_df = to_display_df(df)
+
+    with gr.Blocks(title="にじボイスのキャラと声優さんの対応表デモ") as demo:
+        gr.Markdown(md)
+
+        table = gr.Dataframe(
+            value=display_df,
+            show_row_numbers=True,
+            interactive=False,
+            show_search="search",
+        )
+
+        with gr.Row(equal_height=True):
+            with gr.Column():
+                sel_name = gr.Textbox(label="にじボイスでのキャラ名", interactive=False)
+                tts_choice = gr.Radio(choices=[1, 2, 3], value=1, label="音声例")
+                tts_audio = gr.Audio(label="音声例", interactive=False)
+            with gr.Column():
+                info_md = gr.Markdown(value="## 予想声優", label="声優情報")
+                guess_choice = gr.Radio(choices=[], label="音声例")
+                guess_audio = gr.Audio(label="GUESS", interactive=False)
+
+        def on_row_select_local(evt: gr.SelectData):
+            """
+            表示テーブルの 1 列目（にじボイスでのキャラ名）から speaker を取り出し、
+            meta_by_speaker から staff_id / va を取得して各 UI を更新。
+            """
+            if evt.row_value is None:
+                return (
+                    gr.update(),
+                    gr.update(),
+                    gr.update(),
+                    gr.update(),
+                    gr.update(),
+                    gr.update(),
+                )
+
+            speaker = str(evt.row_value[0]).strip()  # HEADERS[0]
+            meta = meta_by_speaker.get(speaker, {})
+            staff_id = meta.get("staff_id", "")
+            va_value = meta.get("va", "")
+
+            # 左(TTS)
+            tts_default = 1
+            tts_file = tts_path_for(speaker, tts_default)
+
+            # 右上（情報Markdown）
+            md = build_vndb_markdown(staff_id, va_value)
+
+            # 右(guess)
+            choices = guess_numbers_for(speaker)
+            guess_default = choices[0] if choices else None
+            guess_file = (
+                guess_path_for(speaker, guess_default) if guess_default else None
+            )
+
+            return (
+                speaker,  # Textbox
+                gr.Radio(choices=[1, 2, 3], value=tts_default),
+                (tts_file if tts_file else None),  # 左 Audio
+                md,  # 右上 Markdown
+                gr.Radio(choices=choices, value=guess_default),
+                (guess_file if guess_file else None),  # 右 Audio
+            )
+
+        table.select(
+            on_row_select_local,
+            inputs=None,
+            outputs=[
+                sel_name,
+                tts_choice,
+                tts_audio,
+                info_md,
+                guess_choice,
+                guess_audio,
+            ],
+        )
+
+        tts_choice.change(on_tts_pick, [sel_name, tts_choice], tts_audio)
+        guess_choice.change(on_guess_pick, [sel_name, guess_choice], guess_audio)
+
+    return demo
+
+
+if __name__ == "__main__":
+    demo = build_demo(DATA_CSV)
+    demo.launch()
diff --git a/data.csv b/data.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ce51defacd18def717f97ce7e49e5f620f5dcab2
--- /dev/null
+++ b/data.csv
@@ -0,0 +1,125 @@
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