Align infer defaults with generation config and force ja translate

infer.py

@@ -56,7 +56,6 @@ def write_lrc(segments: Iterable, output_path: Path) -> None:
 def transcribe_file(
     model: WhisperModel,
     audio_path: Path,
-    language: str | None,
     beam_size: int,
     vad: bool,
     vad_parameters: dict | None,
@@ -64,10 +63,11 @@ def transcribe_file(
 ) -> tuple[list, str, float]:
     segments_iter, info = model.transcribe(
         str(audio_path),
+        task="translate",
         beam_size=beam_size,
         vad_filter=vad,
         vad_parameters=vad_parameters if vad else None,
-        language=language,
+        language="ja",
         **(extra_generation_args or {}),
     )
     print(f"[{audio_path.name}] Detected language: {info.language} (prob={info.language_probability:.2f})")
@@ -97,14 +97,13 @@ def parse_args() -> argparse.Namespace:
         default="mp3",
         help="Path to an audio file or directory (default: ./mp3).",
     )
-    parser.add_argument("--language", help="Language code (e.g., zh, en). Default: ja.", default="ja")
     parser.add_argument("--beam-size", type=int, default=5, help="Beam size for decoding.")
     parser.add_argument("--no-vad", action="store_true", help="Disable VAD (voice activity detection) filtering.")
     parser.add_argument(
         "--vad-threshold",
         type=float,
-        default=0.35,
-        help="Speech probability threshold for VAD. Lower is less aggressive (default: 0.35).",
+        default=0.5,
+        help="Speech probability threshold for VAD. Lower is less aggressive (default: 0.5).",
     )
     parser.add_argument(
         "--vad-neg-threshold",
@@ -185,7 +184,7 @@ def main() -> None:
         )
 
     generation_args: dict[str, Any] = {
-        # "max_initial_timestamp": 10,
+        "max_initial_timestamp": 30,
         "repetition_penalty": 1.1,
     }
 
@@ -195,7 +194,6 @@ def main() -> None:
             segments, _, _ = transcribe_file(
                 model=model,
                 audio_path=audio_path,
-                language=args.language,
                 beam_size=args.beam_size,
                 vad=not args.no_vad,
                 vad_parameters=vad_parameters,