[唤醒灵敏度与端点恢复]：完成唤醒提示顺序和Hybrid VAD优化，包含阈值默认值、缓冲时序和测试覆盖

src/owner_voice_pet/vad.py

@@ -157,6 +157,53 @@ class SherpaOnnxVadProvider:
             self._model.reset()
 
 
+class HybridVadProvider:
+    """Combine local model VAD with energy fallback for live microphone variance."""
+
+    def __init__(self, primary: Any, fallback: Any) -> None:
+        self.primary = primary
+        self.fallback = fallback
+        self.loaded = False
+        self._speech_ms = 0
+        self._silence_ms = 0
+
+    def load(self) -> None:
+        self.primary.load()
+        self.fallback.load()
+        self.loaded = True
+
+    def analyze(self, frame: AudioFrame) -> VadResult:
+        if not self.loaded:
+            raise ProviderError(
+                ErrorCode.VAD_MODEL_LOAD_FAILED,
+                "hybrid VAD provider is not loaded",
+                False,
+                "hybrid-vad",
+                "vad",
+            )
+        primary = self.primary.analyze(frame)
+        fallback = self.fallback.analyze(frame)
+        is_speech = primary.is_speech or fallback.is_speech
+        frame_ms = int(frame.metadata.get("duration_ms", 20))
+        if is_speech:
+            self._speech_ms += frame_ms
+            self._silence_ms = 0
+        else:
+            self._silence_ms += frame_ms
+        return VadResult(
+            is_speech=is_speech,
+            confidence=max(primary.confidence, fallback.confidence),
+            speech_ms=self._speech_ms,
+            silence_ms=self._silence_ms,
+        )
+
+    def reset(self) -> None:
+        self._speech_ms = 0
+        self._silence_ms = 0
+        self.primary.reset()
+        self.fallback.reset()
+
+
 @dataclass(slots=True)
 class VadRecorder:
     provider: Any