feat: Whisper model selector + 16kHz mono recording

- App: AudioSamplingRateAndroid 16000 + AudioChannelsAndroid 1
  → Whisper bekommt direkt sein Ziel-Format, kein Resample mehr
- Bridge: STTEngine.reload() laedt Modell zur Laufzeit neu
  (tiny/base/small/medium/large-v3)
- Bridge: Config-Message triggert Hot-Reload wenn whisperModel sich aendert
- Bridge: Default auf 'medium' (besser als 'small' bei aehnlicher Latenz)
- Diagnostic: Neue Sektion "Whisper (Spracherkennung)" mit Dropdown,
  auto-save bei Auswahl, beim Laden wird der gespeicherte Wert gesetzt
- Diagnostic/Server: send_voice_config merged whisperModel in voice_config.json
- aria.env.example: WHISPER_MODEL + WHISPER_LANGUAGE dokumentiert

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

bridge/aria_bridge.py

@@ -63,7 +63,7 @@ RVS_TLS = os.getenv("RVS_TLS", "true")       # true = wss://, false = ws://
 RVS_TLS_FALLBACK = os.getenv("RVS_TLS_FALLBACK", "true")  # Bei TLS-Fehler ws:// versuchen
 RVS_TOKEN = os.getenv("RVS_TOKEN", "")       # Pairing-Token (gleich wie in der App)
 DIAGNOSTIC_URL = os.getenv("DIAGNOSTIC_URL", "http://127.0.0.1:3001")  # Diagnostic API
-WHISPER_MODEL = os.getenv("WHISPER_MODEL", "small")
+WHISPER_MODEL = os.getenv("WHISPER_MODEL", "medium")
 WHISPER_LANGUAGE = os.getenv("WHISPER_LANGUAGE", "de")
 
 # Audio-Parameter
@@ -330,6 +330,25 @@ class STTEngine:
         self.model = WhisperModel(self.model_size, device="cpu", compute_type="int8")
         logger.info("Whisper-Modell geladen")
 
+    def reload(self, model_size: str) -> bool:
+        """Laedt ein anderes Whisper-Modell (bei Config-Aenderung)."""
+        if model_size == self.model_size and self.model is not None:
+            return False
+        allowed = {"tiny", "base", "small", "medium", "large-v3"}
+        if model_size not in allowed:
+            logger.warning("Ungueltiges Whisper-Modell: %s (erlaubt: %s)", model_size, allowed)
+            return False
+        logger.info("Lade Whisper-Modell neu: %s -> %s", self.model_size, model_size)
+        self.model_size = model_size
+        self.model = None
+        try:
+            self.model = WhisperModel(model_size, device="cpu", compute_type="int8")
+            logger.info("Whisper-Modell '%s' geladen", model_size)
+            return True
+        except Exception:
+            logger.exception("Whisper-Modell '%s' konnte nicht geladen werden", model_size)
+            return False
+
     def transcribe(self, audio_data: np.ndarray) -> str:
         """Transkribiert Audio-Daten zu Text.
 
@@ -502,6 +521,7 @@ class ARIABridge:
         # Komponenten
         self.voice_engine = VoiceEngine(VOICES_DIR)
         self.tts_enabled = True
+        vc: dict = {}
         # Gespeicherte Voice-Config laden
         try:
             vc_path = "/shared/config/voice_config.json"
@@ -520,8 +540,10 @@ class ARIABridge:
                 logger.info("Voice-Config geladen: %s", vc)
         except Exception as e:
             logger.warning("Voice-Config laden fehlgeschlagen: %s", e)
+        # Whisper-Modell: Config hat Vorrang, dann env/Default (medium)
+        whisper_model = vc.get("whisperModel") or self.config.get("WHISPER_MODEL", WHISPER_MODEL)
         self.stt_engine = STTEngine(
-            model_size=self.config.get("WHISPER_MODEL", WHISPER_MODEL),
+            model_size=whisper_model,
             language=self.config.get("WHISPER_LANGUAGE", WHISPER_LANGUAGE),
         )
         self.wake_word = WakeWordDetector()
@@ -1163,6 +1185,15 @@ class ARIABridge:
                 self.voice_engine.speech_speed["thorsten"] = max(0.3, min(2.0, float(payload["speedThorsten"])))
                 logger.info("[rvs] Speed Thorsten: %.1f", self.voice_engine.speech_speed["thorsten"])
                 changed = True
+            whisper_reloaded = False
+            if "whisperModel" in payload:
+                new_model = payload["whisperModel"]
+                if new_model and new_model != self.stt_engine.model_size:
+                    logger.info("[rvs] Whisper-Modell Wechsel: %s -> %s (laedt...)", self.stt_engine.model_size, new_model)
+                    loop = asyncio.get_event_loop()
+                    whisper_reloaded = await loop.run_in_executor(None, self.stt_engine.reload, new_model)
+                    if whisper_reloaded:
+                        changed = True
             # Persistent speichern in Shared Volume
             if changed:
                 try:
@@ -1175,6 +1206,7 @@ class ARIABridge:
                         "xttsVoice": getattr(self, "xtts_voice", ""),
                         "speedRamona": self.voice_engine.speech_speed.get("ramona", 1.0),
                         "speedThorsten": self.voice_engine.speech_speed.get("thorsten", 1.0),
+                        "whisperModel": self.stt_engine.model_size,
                     }
                     with open("/shared/config/voice_config.json", "w") as f:
                         json.dump(config_data, f, indent=2)