release: bump version to 0.1.9.3

Neuer State 'listening' im WakeWordService. Nach endConversation faellt
ARIA nicht direkt zu armed zurueck, sondern ins passive Lauschen fuer
PASSIVE_LISTEN_DEFAULT_MS (Default 30s, in AsyncStorage konfigurierbar).
In dem Fenster braucht Stefan kein Wake-Word mehr — er kann einfach
weitersprechen, Speaker-ID-Gating in der Whisper-Bridge filtert fremde
Stimmen (TV, Frau, Hintergrundgespraeche).

Flow:
  armed → wake → conversing → TTS → resume → (Nichts gesagt) →
  endConversation → enterPassiveListening('listening' + Timer) →
  startPassiveStreamingRecording (kein User-Bubble, kein wake-ready-Sound)
  → Speaker-ID-Gating in Bridge → Speech detected:
    exitPassiveListening('speech') → 'conversing' → normaler Flow
  → Nichts in N Sek:
    Timer feuert → exitPassiveListening('timeout') → 'armed' (Wake an)

Implementation:
- wakeword.ts: WakeWordState += 'listening'. enterPassiveListening +
  exitPassiveListening + onPassiveListen-Callback + Cancel-Timer-Hooks
  in stop(). PASSIVE_LISTEN_DEFAULT_MS/STORAGE_KEY + load/save Helpers.
- ChatScreen.tsx: state-Type um 'listening' erweitert. State-Listener
  schliesst Conversation-Focus auch in 'listening' (Spotify bleibt
  pausiert). onPassiveListen → startPassiveStreamingRecording mit
  noSpeechTimeoutMs=passiveMs. STT-Endpoint-Handler: bei text != ''
  und state=='listening' → exitPassiveListening('speech'); bei
  text == '' und state=='listening' → naechste passive Aufnahme.
  Beim Wechsel listening→armed/off: laufende streaming-Aufnahme
  cancellen damit OpenWakeWord beim Re-Arm das Mic kriegt.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

android/android/app/build.gradle

@@ -79,8 +79,8 @@ android {
         applicationId "com.ariacockpit"
         minSdkVersion rootProject.ext.minSdkVersion
         targetSdkVersion rootProject.ext.targetSdkVersion
-        versionCode 10902
-        versionName "0.1.9.2"
+        versionCode 10903
+        versionName "0.1.9.3"
         // Fallback fuer Libraries mit Product Flavors
         missingDimensionStrategy 'react-native-camera', 'general'
     }

android/package.json

@@ -1,6 +1,6 @@
 {
   "name": "aria-cockpit",
-  "version": "0.1.9.2",
+  "version": "0.1.9.3",
   "private": true,
   "scripts": {
     "android": "react-native run-android",

android/src/components/VoiceIdEnrollment.tsx

@@ -0,0 +1,426 @@
+/**
+ * Voice-ID Enrollment + Status — App-seitig.
+ *
+ * User nimmt 5-7 Samples (je 4s) seiner Stimme auf, App schickt sie an
+ * die whisper-bridge via RVS (voice_id_enroll_request). Bridge berechnet
+ * SpeechBrain-ECAPA-Embeddings, mittelt sie zu einem Fingerprint, speichert
+ * /voice-id/fingerprint.json.
+ *
+ * Verwendung: in SettingsScreen für Section 'voice_id' eingebunden.
+ * Holt Status bei Mount + nach jedem Enroll/Delete neu ab.
+ */
+
+import React, { useCallback, useEffect, useState } from 'react';
+import {
+  ActivityIndicator,
+  Alert,
+  ScrollView,
+  StyleSheet,
+  Text,
+  ToastAndroid,
+  TouchableOpacity,
+  View,
+} from 'react-native';
+
+import audioService from '../services/audio';
+import rvs from '../services/rvs';
+
+const SAMPLE_DURATION_MS = 4000;      // Pro Sample 4s aufnehmen
+const SAMPLES_REQUIRED = 5;           // Mindest-Sampleanzahl fuer Save
+
+type Sample = {
+  base64: string;
+  durationMs: number;
+};
+
+type Status =
+  | { state: 'loading' }
+  | { state: 'unenrolled' }
+  | { state: 'enrolled'; sampleCount: number; durations: number[]; updatedAt: number; dim: number }
+  | { state: 'error'; message: string };
+
+function _newReqId(prefix: string): string {
+  return `${prefix}_${Date.now().toString(36)}_${Math.floor(Math.random() * 1e6).toString(36)}`;
+}
+
+export const VoiceIdEnrollment: React.FC = () => {
+  const [status, setStatus] = useState<Status>({ state: 'loading' });
+  const [samples, setSamples] = useState<Sample[]>([]);
+  const [recording, setRecording] = useState(false);
+  const [recordCountdown, setRecordCountdown] = useState(0);
+  const [enrollPending, setEnrollPending] = useState(false);
+  const [pendingReqId, setPendingReqId] = useState<string | null>(null);
+
+  // Status laden
+  const refreshStatus = useCallback(() => {
+    setStatus({ state: 'loading' });
+    const reqId = _newReqId('vid');
+    setPendingReqId(reqId);
+    rvs.send('voice_id_status_request' as any, { requestId: reqId });
+  }, []);
+
+  useEffect(() => {
+    refreshStatus();
+  }, [refreshStatus]);
+
+  // RVS-Antworten verarbeiten
+  useEffect(() => {
+    const unsub = rvs.onMessage((msg: any) => {
+      if (!msg) return;
+      const p = msg.payload || {};
+      if (msg.type === 'voice_id_status_response') {
+        if (p.ok === false) {
+          setStatus({ state: 'error', message: p.error || 'Whisper-Bridge nicht erreichbar' });
+          return;
+        }
+        if (p.enrolled) {
+          setStatus({
+            state: 'enrolled',
+            sampleCount: p.sample_count || 0,
+            durations: p.sample_durations_s || [],
+            updatedAt: p.updated_at || 0,
+            dim: p.embedding_dim || 0,
+          });
+        } else {
+          setStatus({ state: 'unenrolled' });
+        }
+      } else if (msg.type === 'voice_id_enroll_response') {
+        setEnrollPending(false);
+        if (p.ok === false) {
+          Alert.alert('Enrollment fehlgeschlagen', p.error || 'Unbekannter Fehler');
+          return;
+        }
+        const rejected = (p.rejected || []).length;
+        ToastAndroid.show(
+          `✓ Stimme gespeichert (${p.sample_count} Samples${rejected ? `, ${rejected} verworfen` : ''})`,
+          ToastAndroid.LONG,
+        );
+        setSamples([]);
+        refreshStatus();
+      } else if (msg.type === 'voice_id_delete_response') {
+        ToastAndroid.show(p.removed ? '✓ Stimme gelöscht' : 'Es war keine gespeichert', ToastAndroid.SHORT);
+        refreshStatus();
+      }
+    });
+    return () => unsub();
+  }, [refreshStatus]);
+
+  // Ein Sample aufnehmen — fest 4s, dann auto-stop
+  const recordSample = useCallback(async () => {
+    if (recording || enrollPending) return;
+    setRecording(true);
+    setRecordCountdown(SAMPLE_DURATION_MS / 1000);
+    try {
+      const ok = await audioService.startRecording(false);
+      if (!ok) {
+        ToastAndroid.show('Aufnahme konnte nicht gestartet werden', ToastAndroid.LONG);
+        setRecording(false);
+        setRecordCountdown(0);
+        return;
+      }
+      // Countdown-Timer (rein UI)
+      const tickInterval = setInterval(() => {
+        setRecordCountdown(c => Math.max(0, c - 1));
+      }, 1000);
+      // Auto-Stop nach festen 4s
+      await new Promise(r => setTimeout(r, SAMPLE_DURATION_MS));
+      clearInterval(tickInterval);
+      const result = await audioService.stopRecording();
+      setRecordCountdown(0);
+      setRecording(false);
+      if (!result || !result.base64) {
+        ToastAndroid.show('Aufnahme leer — nochmal probieren', ToastAndroid.LONG);
+        return;
+      }
+      setSamples(prev => [...prev, { base64: result.base64, durationMs: result.durationMs }]);
+    } catch (err: any) {
+      console.warn('[VoiceId] recordSample:', err);
+      try { await audioService.cancelRecording(); } catch {}
+      setRecording(false);
+      setRecordCountdown(0);
+      ToastAndroid.show('Aufnahmefehler: ' + (err?.message || err), ToastAndroid.LONG);
+    }
+  }, [recording, enrollPending]);
+
+  const removeSample = useCallback((idx: number) => {
+    setSamples(prev => prev.filter((_, i) => i !== idx));
+  }, []);
+
+  const sendEnrollment = useCallback(() => {
+    if (samples.length < SAMPLES_REQUIRED) {
+      Alert.alert('Noch nicht genug',
+        `Bitte mindestens ${SAMPLES_REQUIRED} Samples aufnehmen — aktuell ${samples.length}.`);
+      return;
+    }
+    if (enrollPending) return;
+    setEnrollPending(true);
+    const reqId = _newReqId('videnroll');
+    rvs.send('voice_id_enroll_request' as any, {
+      requestId: reqId,
+      samples: samples.map(s => s.base64),
+    });
+    // Sicherheits-Timeout: wenn nach 60s nichts kommt, freigeben
+    setTimeout(() => {
+      setEnrollPending(prev => {
+        if (prev) {
+          ToastAndroid.show('Enrollment-Timeout — bitte erneut versuchen', ToastAndroid.LONG);
+        }
+        return false;
+      });
+    }, 60_000);
+  }, [samples, enrollPending]);
+
+  const deleteFingerprint = useCallback(() => {
+    Alert.alert(
+      'Stimme löschen?',
+      'Danach muss ARIA neu enrolled werden, sonst greift Speaker-ID-Filter nicht.',
+      [
+        { text: 'Abbrechen', style: 'cancel' },
+        {
+          text: 'Löschen', style: 'destructive', onPress: () => {
+            const reqId = _newReqId('viddel');
+            rvs.send('voice_id_delete_request' as any, { requestId: reqId });
+          },
+        },
+      ],
+    );
+  }, []);
+
+  // ── Render ──────────────────────────────────────────────
+
+  return (
+    <ScrollView contentContainerStyle={{ paddingBottom: 30 }}>
+      <Text style={s.intro}>
+        ARIA erkennt deine Stimme an einem Fingerprint (SpeechBrain ECAPA-TDNN, 192 Dimensionen).
+        Andere Sprecher (TV, Hintergrund, andere Personen) werden gefiltert — keine Brain-Calls,
+        keine Tokens. {'\n\n'}
+        Sprich {SAMPLES_REQUIRED} Mal je {SAMPLE_DURATION_MS / 1000}s ganz normal — verschiedene
+        Sätze, ruhige Umgebung empfohlen.
+      </Text>
+
+      {/* Status-Karte */}
+      <View style={s.card}>
+        <Text style={s.cardLabel}>Status</Text>
+        {status.state === 'loading' && (
+          <View style={{ flexDirection: 'row', alignItems: 'center', gap: 8 }}>
+            <ActivityIndicator color="#0096FF" />
+            <Text style={s.statusText}>Wird abgefragt...</Text>
+          </View>
+        )}
+        {status.state === 'unenrolled' && (
+          <Text style={[s.statusText, { color: '#FFD60A' }]}>○ Nicht enrolled — Stimme einrichten ↓</Text>
+        )}
+        {status.state === 'enrolled' && (
+          <>
+            <Text style={[s.statusText, { color: '#34C759' }]}>
+              ✓ Enrolled — {status.sampleCount} Samples
+              ({status.durations.reduce((a, b) => a + b, 0).toFixed(1)}s gesamt)
+            </Text>
+            <Text style={s.statusSub}>
+              Aktualisiert {new Date(status.updatedAt * 1000).toLocaleString('de-DE')} · dim={status.dim}
+            </Text>
+          </>
+        )}
+        {status.state === 'error' && (
+          <Text style={[s.statusText, { color: '#FF6E6E' }]}>⚠ {status.message}</Text>
+        )}
+      </View>
+
+      {/* Aufnahme-Bereich */}
+      <View style={s.card}>
+        <Text style={s.cardLabel}>Samples ({samples.length}/{SAMPLES_REQUIRED})</Text>
+        {samples.length === 0 && !recording && (
+          <Text style={s.hint}>Tipp: sprich klare normale Sätze, je 3-4 Sekunden Audio.</Text>
+        )}
+        {samples.map((sample, idx) => (
+          <View key={idx} style={s.sampleRow}>
+            <Text style={s.sampleText}>
+              Sample {idx + 1} · {(sample.durationMs / 1000).toFixed(1)}s
+            </Text>
+            <TouchableOpacity onPress={() => removeSample(idx)} disabled={enrollPending}>
+              <Text style={{ color: '#FF6E6E', fontSize: 18 }}>✕</Text>
+            </TouchableOpacity>
+          </View>
+        ))}
+
+        <TouchableOpacity
+          onPress={recordSample}
+          disabled={recording || enrollPending}
+          style={[s.recordBtn, (recording || enrollPending) && { opacity: 0.5 }]}
+        >
+          {recording ? (
+            <>
+              <ActivityIndicator color="#fff" />
+              <Text style={s.recordBtnText}>Aufnahme läuft… {recordCountdown}s</Text>
+            </>
+          ) : (
+            <Text style={s.recordBtnText}>⏺ Sample {samples.length + 1} aufnehmen</Text>
+          )}
+        </TouchableOpacity>
+
+        {samples.length > 0 && !recording && (
+          <TouchableOpacity
+            onPress={() => setSamples([])}
+            disabled={enrollPending}
+            style={s.resetBtn}
+          >
+            <Text style={s.resetBtnText}>Alle verwerfen</Text>
+          </TouchableOpacity>
+        )}
+      </View>
+
+      {/* Aktionen */}
+      <View style={{ flexDirection: 'row', gap: 8, marginTop: 8 }}>
+        <TouchableOpacity
+          onPress={sendEnrollment}
+          disabled={samples.length < SAMPLES_REQUIRED || enrollPending}
+          style={[
+            s.primaryBtn,
+            (samples.length < SAMPLES_REQUIRED || enrollPending) && { opacity: 0.4 },
+          ]}
+        >
+          {enrollPending ? (
+            <>
+              <ActivityIndicator color="#fff" />
+              <Text style={s.primaryBtnText}>Wird verarbeitet…</Text>
+            </>
+          ) : (
+            <Text style={s.primaryBtnText}>
+              ✓ Speichern ({samples.length}/{SAMPLES_REQUIRED})
+            </Text>
+          )}
+        </TouchableOpacity>
+      </View>
+
+      {/* Verwaltung */}
+      {status.state === 'enrolled' && (
+        <View style={[s.card, { marginTop: 20 }]}>
+          <Text style={s.cardLabel}>Verwaltung</Text>
+          <TouchableOpacity onPress={refreshStatus} style={s.secondaryBtn}>
+            <Text style={s.secondaryBtnText}>🔄 Status aktualisieren</Text>
+          </TouchableOpacity>
+          <TouchableOpacity onPress={deleteFingerprint} style={s.dangerBtn}>
+            <Text style={s.dangerBtnText}>🗑 Fingerprint löschen (Re-Enrollment nötig)</Text>
+          </TouchableOpacity>
+        </View>
+      )}
+    </ScrollView>
+  );
+};
+
+const s = StyleSheet.create({
+  intro: {
+    color: '#8888AA',
+    fontSize: 13,
+    lineHeight: 19,
+    marginBottom: 16,
+    paddingHorizontal: 4,
+  },
+  card: {
+    backgroundColor: 'rgba(30,30,46,0.6)',
+    borderRadius: 8,
+    padding: 14,
+    marginBottom: 10,
+  },
+  cardLabel: {
+    color: '#8888AA',
+    fontSize: 11,
+    fontWeight: '700',
+    textTransform: 'uppercase',
+    letterSpacing: 0.5,
+    marginBottom: 8,
+  },
+  statusText: {
+    color: '#E0E0F0',
+    fontSize: 14,
+    fontWeight: '600',
+  },
+  statusSub: {
+    color: '#555570',
+    fontSize: 11,
+    marginTop: 4,
+  },
+  hint: {
+    color: '#555570',
+    fontSize: 12,
+    fontStyle: 'italic',
+    marginBottom: 8,
+  },
+  sampleRow: {
+    flexDirection: 'row',
+    justifyContent: 'space-between',
+    alignItems: 'center',
+    paddingVertical: 6,
+    borderBottomWidth: 1,
+    borderColor: '#2A2A3E',
+  },
+  sampleText: {
+    color: '#E0E0F0',
+    fontSize: 13,
+  },
+  recordBtn: {
+    flexDirection: 'row',
+    alignItems: 'center',
+    justifyContent: 'center',
+    gap: 8,
+    backgroundColor: '#E55C5C',
+    borderRadius: 8,
+    paddingVertical: 14,
+    marginTop: 12,
+  },
+  recordBtnText: {
+    color: '#fff',
+    fontSize: 15,
+    fontWeight: '700',
+  },
+  resetBtn: {
+    alignItems: 'center',
+    paddingVertical: 8,
+    marginTop: 6,
+  },
+  resetBtnText: {
+    color: '#FFD60A',
+    fontSize: 12,
+  },
+  primaryBtn: {
+    flex: 1,
+    flexDirection: 'row',
+    alignItems: 'center',
+    justifyContent: 'center',
+    gap: 8,
+    backgroundColor: '#34C759',
+    borderRadius: 8,
+    paddingVertical: 14,
+  },
+  primaryBtnText: {
+    color: '#fff',
+    fontSize: 15,
+    fontWeight: '700',
+  },
+  secondaryBtn: {
+    backgroundColor: 'rgba(0,150,255,0.15)',
+    borderRadius: 6,
+    paddingVertical: 10,
+    alignItems: 'center',
+    marginTop: 6,
+  },
+  secondaryBtnText: {
+    color: '#0096FF',
+    fontSize: 13,
+    fontWeight: '600',
+  },
+  dangerBtn: {
+    backgroundColor: 'rgba(229,92,92,0.15)',
+    borderRadius: 6,
+    paddingVertical: 10,
+    alignItems: 'center',
+    marginTop: 6,
+  },
+  dangerBtnText: {
+    color: '#E55C5C',
+    fontSize: 13,
+    fontWeight: '600',
+  },
+});
+
+export default VoiceIdEnrollment;

android/src/screens/ChatScreen.tsx

@@ -35,7 +35,7 @@ import MemoryBrowser from '../components/MemoryBrowser';
 import ErrorBoundary from '../components/ErrorBoundary';
 import rvs, { RVSMessage, ConnectionState } from '../services/rvs';
 import audioService from '../services/audio';
-import wakeWordService from '../services/wakeword';
+import wakeWordService, { loadPassiveListenMs } from '../services/wakeword';
 import phoneCallService from '../services/phoneCall';
 import { playWakeReadySound } from '../services/wakeReadySound';
 import {
@@ -273,7 +273,7 @@ const ChatScreen: React.FC = () => {
   const [gpsEnabled, setGpsEnabled] = useState(false);
   const [wakeWordActive, setWakeWordActive] = useState(false);
   // Genauer State (off/armed/conversing) fuer UI-Feedback am Button
-  const [wakeWordState, setWakeWordState] = useState<'off' | 'armed' | 'conversing'>('off');
+  const [wakeWordState, setWakeWordState] = useState<'off' | 'armed' | 'conversing' | 'listening'>('off');
   const [fullscreenImage, setFullscreenImage] = useState<string | null>(null);
   const [memoryDetailId, setMemoryDetailId] = useState<string | null>(null);
   const [inboxVisible, setInboxVisible] = useState(false);
@@ -487,9 +487,16 @@ const ChatScreen: React.FC = () => {
       // Conversation-Focus an Wake-Word-State koppeln: solange wir aktiv im
       // Dialog sind, soll Spotify dauerhaft gepaust bleiben (auch ueber
       // Render-Pausen + zwischen Antworten hinweg). Sobald wir zurueck nach
-      // 'armed' oder 'off' fallen, darf Spotify wieder.
-      if (s === 'conversing') audioService.acquireConversationFocus();
+      // 'armed' oder 'off' fallen, darf Spotify wieder. 'listening' soll
+      // Spotify ebenfalls leise halten (User darf jederzeit weitersprechen).
+      if (s === 'conversing' || s === 'listening') audioService.acquireConversationFocus();
       else audioService.releaseConversationFocus();
+      // Beim Verlassen von 'listening' (Timer abgelaufen) eine ggf. noch
+      // laufende passive Streaming-Aufnahme killen, sonst hat OpenWakeWord
+      // keinen Zugriff aufs Mic beim Re-Arm.
+      if ((s === 'armed' || s === 'off') && audioService.isStreamingRecording()) {
+        audioService.cancelStreamingRecording('wakeword-state-' + s);
+      }
       // Foreground-Service-Slot 'wake' — solange das Ohr ueberhaupt aktiv ist
       // (armed oder conversing), soll der App-Prozess im Hintergrund am Leben
       // bleiben damit Mikro-Lauschen + Aufnahme weiterlaufen.
@@ -1346,12 +1353,18 @@ const ChatScreen: React.FC = () => {
     //   - text != ''  → Whisper-Bridge hat ML-Endpoint erkannt, Text liegt vor.
     //                   aria-bridge bekommt das gleiche Event und triggert Brain
     //                   direkt. App muss nix mehr senden.
-    //   - text == ''  → cancelStreamingRecording (no-speech / hardcap / error).
-    //                   Konversation beenden wie frueher der "kein Speech"-Fall.
+    //   - text == ''  → cancelStreamingRecording (no-speech / hardcap / error /
+    //                   speaker_mismatch). Konversation beenden, oder bei
+    //                   passive-listening: nochmal lauschen.
     const unsubEndpoint = audioService.onSttEndpoint((ev) => {
       if (ev.text && ev.text.trim()) {
         console.log('[Chat] STT-Endpoint: %r (reason=%s, %dms, %.1fs Audio)',
                     ev.text.slice(0, 80), ev.reason, ev.sttMs, ev.durationS);
+        // Wenn passive lauschend: User hat tatsaechlich was gesagt → uebergang
+        // zu 'conversing' damit der normale Flow greift (TTS, resume, etc.)
+        if (wakeWordService.getState() === 'listening') {
+          wakeWordService.exitPassiveListening('speech').catch(() => {});
+        }
         // Brain laeuft via aria-bridge — wir warten auf chat(sender=stt) +
         // chat(sender=aria) wie im Legacy-Pfad.
       } else {
@@ -1361,11 +1374,28 @@ const ChatScreen: React.FC = () => {
         if (ev.audioRequestId) {
           setMessages(prev => prev.filter(m => m.audioRequestId !== ev.audioRequestId));
         }
-        wakeWordService.endConversation();
-        if (!wakeWordService.isActive()) setWakeWordActive(false);
+        // Bei Passive-Listen + speaker_mismatch oder no-speech: erneut passiv
+        // lauschen (Timer im wakeword-service laeuft weiter, regelt das Ende).
+        // Sonst endConversation wie bisher.
+        if (wakeWordService.getState() === 'listening') {
+          console.log('[Chat] Passive-Listen: leeres Endpoint — naechste passive Aufnahme');
+          startPassiveStreamingRecording();
+        } else {
+          wakeWordService.endConversation();
+          if (!wakeWordService.isActive()) setWakeWordActive(false);
+        }
       }
     });
 
+    // Passive-Listen-Callback: Wake-Word-Service hat in den passiven Modus
+    // geschaltet (nach endConversation). Wir starten eine streaming-Aufnahme
+    // OHNE User-Bubble + ohne wake-ready-Sound. Speaker-ID-Gating in der
+    // Whisper-Bridge filtert fremde Stimmen weg.
+    const unsubPassive = wakeWordService.onPassiveListen(() => {
+      console.log('[Chat] Passive-Listen aktiviert — starte stille Streaming-Aufnahme');
+      startPassiveStreamingRecording();
+    });
+
     // Barge-In via Wake-Word: User sagt "Computer" waehrend ARIA spricht.
     // Wake-Word-Service hat bei TTS-Start parallel zu lauschen begonnen
     // (mit AcousticEchoCanceler damit ARIAs eigene Stimme nicht triggert).
@@ -1430,11 +1460,38 @@ const ChatScreen: React.FC = () => {
       unsubWake();
       unsubEndpoint();
       unsubBarge();
+      unsubPassive();
       unsubTtsStart();
       unsubTtsEnd();
     };
   }, [wakeWordActive]);
 
+  // Passive-Listen-Aufnahme: ohne User-Bubble, ohne Wake-Sound, Speaker-ID-
+  // Gating in der Whisper-Bridge entscheidet ob Stefan spricht oder z.B.
+  // die Frau / TV. Bei text != '' → wakeWordService.exitPassiveListening('speech')
+  // schaltet auf conversing, Brain antwortet, TTS spielt, resume → endConv →
+  // ... und passive listening startet von vorne (mit frischem Timer).
+  // useCallback damit der useEffect oben die Funktion stabil capturen kann.
+  const startPassiveStreamingRecording = useCallback(async () => {
+    const audioRequestId = `audio_passive_${Date.now()}_${Math.floor(Math.random() * 100000)}`;
+    const location = await getCurrentLocation();
+    const passiveMs = await loadPassiveListenMs();
+    const { ok } = await audioService.startStreamingRecording({
+      audioRequestId,
+      voice: localXttsVoiceRef.current,
+      speed: ttsSpeedRef.current,
+      interrupted: false,
+      location: location || null,
+      noSpeechTimeoutMs: Math.min(passiveMs, 30000),
+      endpointMs: 1500,
+      hardCapMs: Math.max(passiveMs + 5000, 35000),
+    });
+    if (!ok) {
+      console.warn('[Chat] passive streaming start failed — exit passive listening');
+      wakeWordService.exitPassiveListening('manual').catch(() => {});
+    }
+  }, []);
+
   // Wake Word Toggle Handler
   const toggleWakeWord = useCallback(async () => {
     if (wakeWordActive) {

android/src/screens/SettingsScreen.tsx

@@ -91,6 +91,7 @@ import MemoryBrowser from '../components/MemoryBrowser';
 import TriggerBrowser from '../components/TriggerBrowser';
 import SkillBrowser from '../components/SkillBrowser';
 import OAuthBrowser from '../components/OAuthBrowser';
+import VoiceIdEnrollment from '../components/VoiceIdEnrollment';
 import { isVerboseLogging, setVerboseLogging, isDebugLogsToBridge, setDebugLogsToBridge, APP_LOG_EVENT } from '../services/logger';
 import {
   isWakeReadySoundEnabled,
@@ -136,6 +137,7 @@ const SETTINGS_SECTIONS = [
   { id: 'general',      icon: '⚙️', label: 'Allgemein',      desc: 'Betriebsmodus, GPS-Standort' },
   { id: 'voice_input',  icon: '🎙️', label: 'Spracheingabe',  desc: 'Stille-Toleranz, Aufnahmedauer' },
   { id: 'wake_word',    icon: '👂', label: 'Wake-Word',      desc: 'Wake-Word-Auswahl' },
+  { id: 'voice_id',     icon: '🎤', label: 'Stimme einrichten', desc: 'Sprecher-Erkennung — nur deine Stimme triggert ARIA' },
   { id: 'voice_output', icon: '🔊', label: 'Sprachausgabe',  desc: 'Stimmen, Pre-Roll, Geschwindigkeit' },
   { id: 'storage',      icon: '📁', label: 'Speicher',       desc: 'Anhang-Speicherort, Auto-Download' },
   { id: 'files',        icon: '📂', label: 'Dateien',        desc: 'ARIA- und User-Dateien — anzeigen, löschen' },
@@ -1836,6 +1838,12 @@ const SettingsScreen: React.FC = () => {
       </View>
       </>)}
 
+      {/* === Voice-ID Enrollment (Sprecher-Erkennung) === */}
+      {currentSection === 'voice_id' && (<>
+      <Text style={styles.sectionTitle}>Stimme einrichten</Text>
+      <VoiceIdEnrollment />
+      </>)}
+
       {/* === Sprachausgabe (geraetelokal) === */}
       {currentSection === 'voice_output' && (<>
       <Text style={styles.sectionTitle}>Sprachausgabe</Text>

android/src/services/wakeword.ts

@@ -26,8 +26,30 @@ import { acquireBackgroundAudio } from './backgroundAudio';
 
 type WakeWordCallback = () => void;
 type StateCallback = (state: WakeWordState) => void;
+type PassiveListenCallback = () => void;
 
-export type WakeWordState = 'off' | 'armed' | 'conversing';
+export type WakeWordState = 'off' | 'armed' | 'conversing' | 'listening';
+
+/** Default-Dauer fuer den Passive-Listen-Modus nach einer Konversation —
+ *  in dem Fenster braucht's kein Wake-Word, Speaker-ID-Filter haelt
+ *  fremde Stimmen raus (TV, Familie). 30s default; konfigurierbar. */
+export const PASSIVE_LISTEN_DEFAULT_MS = 30_000;
+export const PASSIVE_LISTEN_STORAGE_KEY = 'aria_passive_listen_ms';
+
+export async function loadPassiveListenMs(): Promise<number> {
+  try {
+    const raw = await AsyncStorage.getItem(PASSIVE_LISTEN_STORAGE_KEY);
+    if (raw) {
+      const n = parseInt(raw, 10);
+      if (isFinite(n) && n >= 0 && n <= 120_000) return n;
+    }
+  } catch {}
+  return PASSIVE_LISTEN_DEFAULT_MS;
+}
+
+export async function savePassiveListenMs(ms: number): Promise<void> {
+  await AsyncStorage.setItem(PASSIVE_LISTEN_STORAGE_KEY, String(ms));
+}
 
 export const WAKE_KEYWORD_STORAGE = 'aria_wake_keyword';
 
@@ -103,6 +125,12 @@ class WakeWordService {
    *  Ausnahme: bargeListening → Barge-In ist ein legitimer neuer Trigger
    *  waehrend ARIA noch redet, NICHT vom Guard blockieren. */
   private detectionInProgress: boolean = false;
+  /** Passive-Listen-Timer: feuert nach PASSIVE_LISTEN_MS ohne Stefan-Speech,
+   *  beendet den listening-State und geht zurueck zu armed. */
+  private passiveListenTimer: ReturnType<typeof setTimeout> | null = null;
+  /** Callbacks fuer den Eintritt in Passive-Listen — ChatScreen startet
+   *  hier eine streaming-Aufnahme OHNE User-Bubble (passiv lauschen). */
+  private passiveListenCallbacks: PassiveListenCallback[] = [];
 
   private keyword: WakeKeyword = DEFAULT_KEYWORD;
   private nativeReady: boolean = false;
@@ -225,6 +253,7 @@ class WakeWordService {
   /** Komplett ausschalten (Ohr abschalten) */
   async stop(): Promise<void> {
     console.log('[WakeWord] Ohr deaktiviert');
+    this.cancelPassiveListenTimer();
     if (this.nativeReady && OpenWakeWord) {
       try { await OpenWakeWord.stop(); } catch {}
     }
@@ -407,6 +436,17 @@ class WakeWordService {
     this.bargeListening = false;
     import('./logger').then(m => m.reportAppDebug('wake.end',
       `endConversation called, wasBarge=${wasBarge}, nativeReady=${this.nativeReady}`)).catch(()=>{});
+
+    // Passive-Listen aktiv? Dann nicht direkt zu armed — passive lauschen
+    // fuer N Sekunden, dann erst Wake-Word wieder aktivieren. Speaker-ID
+    // (Phase 3) filtert fremde Stimmen weg, der User kann ohne erneute
+    // Anrede weitersprechen.
+    const passiveMs = await loadPassiveListenMs();
+    if (passiveMs > 0 && this.nativeReady) {
+      this.enterPassiveListening(passiveMs);
+      return;
+    }
+
     if (this.nativeReady && OpenWakeWord) {
       // Wenn wakeword schon laeuft (war Barge-Listener waehrend TTS):
       // OpenWakeWord.start() ist idempotent (Kotlin checkt running.get()
@@ -435,6 +475,80 @@ class WakeWordService {
     this.setState('off');
   }
 
+  /** Eintritt in den Passive-Listen-Modus: state='listening', Timer fuer
+   *  Auto-Ende setzen, Callbacks feuern damit ChatScreen die passive
+   *  Streaming-Aufnahme startet. OpenWakeWord bleibt AUS (Mic-Exklusivitaet —
+   *  audioService braucht das Mikro fuer die passive Aufnahme).
+   *  Speaker-ID-Gating (Phase 3) filtert fremde Stimmen auf der Bridge. */
+  private enterPassiveListening(durationMs: number): void {
+    this.cancelPassiveListenTimer();
+    this.setState('listening');
+    const seconds = Math.round(durationMs / 1000);
+    console.log('[WakeWord] Passive-Listen aktiv (%ds) — Speaker-ID gefiltert', seconds);
+    import('./logger').then(m => m.reportAppDebug('wake.passive',
+      `entered listening for ${seconds}s, cb-count=${this.passiveListenCallbacks.length}`)).catch(()=>{});
+    ToastAndroid.show(`🎧 ${seconds}s lauscht — sprich einfach weiter`, ToastAndroid.SHORT);
+    this.passiveListenTimer = setTimeout(() => {
+      this.passiveListenTimer = null;
+      this.exitPassiveListening('timeout').catch(() => {});
+    }, durationMs);
+    this.passiveListenCallbacks.forEach(cb => {
+      try { cb(); } catch (e) { console.warn('[WakeWord] passive cb err:', e); }
+    });
+  }
+
+  /** Verlassen des Passive-Listen-Modus.
+   *  reason='speech' → User hat was gesagt (STT-Endpoint mit text) → uebergang
+   *    in 'conversing' (Brain antwortet, TTS spielt, dann resume → endConversation
+   *    → wieder passive listening, repeat).
+   *  reason='timeout' → 30s nichts gehoert → zurueck zu armed (Wake-Word wieder an).
+   *  reason='manual' → User hat App geschlossen / stopped → zurueck zu armed. */
+  async exitPassiveListening(reason: 'timeout' | 'speech' | 'manual'): Promise<void> {
+    if (this.state !== 'listening') return;
+    this.cancelPassiveListenTimer();
+    console.log('[WakeWord] Passive-Listen Ende (reason=%s)', reason);
+    import('./logger').then(m => m.reportAppDebug('wake.passive',
+      `exit reason=${reason}`)).catch(()=>{});
+
+    if (reason === 'speech') {
+      // Wechsel zu 'conversing' damit das Standard-Conversation-Flow greift
+      // (Brain-Response, TTS, resume etc.). Wake-Word bleibt aus (Mic belegt).
+      this.setState('conversing');
+      return;
+    }
+
+    // timeout oder manual → Wake-Word reaktivieren, armed-State.
+    if (this.nativeReady && OpenWakeWord) {
+      try {
+        await OpenWakeWord.start();
+        console.log('[WakeWord] zurueck zu armed nach passive-listen');
+        ToastAndroid.show(`Lausche wieder auf "${KEYWORD_LABELS[this.keyword]}"`, ToastAndroid.SHORT);
+        this.setState('armed');
+        return;
+      } catch (err) {
+        console.warn('[WakeWord] re-arm nach passive-listen failed:', err);
+      }
+    }
+    this.setState('off');
+  }
+
+  private cancelPassiveListenTimer(): void {
+    if (this.passiveListenTimer) {
+      clearTimeout(this.passiveListenTimer);
+      this.passiveListenTimer = null;
+    }
+  }
+
+  /** Subscribe auf Passive-Listen-Events: feuert wenn der Service in den
+   *  passiven Modus eintritt. ChatScreen startet hier eine streaming-
+   *  Aufnahme OHNE User-Bubble (passiv lauschen). */
+  onPassiveListen(callback: PassiveListenCallback): () => void {
+    this.passiveListenCallbacks.push(callback);
+    return () => {
+      this.passiveListenCallbacks = this.passiveListenCallbacks.filter(c => c !== callback);
+    };
+  }
+
   /** Wenn ein conversing-State auf einem Wake-Word-Trigger juenger als
    *  maxAgeMs basiert: false-positive verwerfen, zurueck zu armed.
    *  Wird vom ChatScreen aufgerufen wenn die App aus laengerem Hintergrund

diagnostic/index.html

@@ -764,6 +764,42 @@
       </div>
     </div>
 
+    <!-- Voice-ID (Sprecher-Erkennung) -->
+    <div class="settings-section">
+      <h2>Voice-ID (Sprecher-Erkennung)</h2>
+      <div style="font-size:11px;color:#8888AA;margin-bottom:8px;">
+        ARIA erkennt Stefans Stimme anhand eines Fingerprints (SpeechBrain ECAPA-TDNN).
+        Andere Sprecher (TV, Hintergrund-Gespraeche) werden gefiltert — keine Brain-
+        Calls, keine Tokens. Enrollment passiert in der App (Settings → Stimme einrichten),
+        weil das Handy-Mikro auch im Betrieb hoert.
+      </div>
+      <div class="card" style="max-width:500px;">
+        <div id="voice-id-status" style="font-size:13px;color:#E0E0F0;margin-bottom:10px;">
+          Status wird geladen...
+        </div>
+        <div style="display:flex;align-items:center;gap:12px;margin-bottom:8px;">
+          <label style="color:#8888AA;font-size:12px;min-width:130px;">Match-Threshold:</label>
+          <input type="range" id="diag-voice-id-threshold" min="0.30" max="0.70" step="0.05" value="0.50"
+                 oninput="document.getElementById('voice-id-threshold-display').textContent = this.value"
+                 onchange="sendVoiceConfig()"
+                 style="flex:1;">
+          <span id="voice-id-threshold-display" style="color:#E0E0F0;font-family:monospace;min-width:40px;text-align:right;">0.50</span>
+        </div>
+        <div style="font-size:10px;color:#555570;margin-bottom:12px;">
+          Niedriger = mehr Treffer auch bei Nebengeraeuschen (false-positives).
+          Hoeher = strenger, kann Stefan auch mal verpassen. 0.50 ist konservativer Default.
+        </div>
+        <div style="display:flex;gap:8px;">
+          <button class="btn secondary" onclick="refreshVoiceIdStatus()" style="padding:6px 14px;font-size:12px;">
+            🔄 Status aktualisieren
+          </button>
+          <button class="btn danger" onclick="deleteVoiceId()" style="padding:6px 14px;font-size:12px;">
+            🗑 Fingerprint löschen
+          </button>
+        </div>
+      </div>
+    </div>
+
     <!-- Runtime-Konfiguration -->
     <div class="settings-section">
       <h2>Runtime-Konfiguration</h2>
@@ -1475,6 +1511,46 @@
           setIfPresent('diag-flux-keyword-raw', msg.fluxKeywordRaw);
           setIfPresent('diag-flux-keyword-switch', msg.fluxKeywordSwitch);
           setIfPresent('diag-flux-hf-token', msg.huggingfaceToken);
+          // Voice-ID-Threshold wiederherstellen (Default 0.50)
+          if (msg.voiceIdThreshold !== undefined && msg.voiceIdThreshold !== null) {
+            const slider = document.getElementById('diag-voice-id-threshold');
+            const display = document.getElementById('voice-id-threshold-display');
+            if (slider) slider.value = msg.voiceIdThreshold;
+            if (display) display.textContent = Number(msg.voiceIdThreshold).toFixed(2);
+          }
+          return;
+        }
+
+        if (msg.type === 'voice_id_status_response') {
+          const el = document.getElementById('voice-id-status');
+          if (!el) return;
+          if (msg.payload && msg.payload.ok === false) {
+            el.innerHTML = '<span style="color:#FF6E6E;">⚠ Whisper-Bridge nicht erreichbar: ' +
+                           (msg.payload.error || 'unbekannt') + '</span>';
+            return;
+          }
+          const p = msg.payload || msg;
+          if (p.enrolled) {
+            const when = p.updated_at ? new Date(p.updated_at * 1000).toLocaleString('de-DE') : '?';
+            const totalSec = (p.sample_durations_s || []).reduce((a, b) => a + b, 0);
+            el.innerHTML = '<span style="color:#34C759;">✓ Enrolled</span> · ' +
+                           p.sample_count + ' Samples (' + totalSec.toFixed(1) + 's) · ' +
+                           'aktualisiert ' + when + ' · dim=' + (p.embedding_dim || '?');
+          } else {
+            el.innerHTML = '<span style="color:#FFD60A;">○ Nicht enrolled</span> — ' +
+                           'in der App unter "Stimme einrichten" 5-10× je 3s aufnehmen.';
+          }
+          return;
+        }
+
+        if (msg.type === 'voice_id_delete_response') {
+          const p = msg.payload || msg;
+          if (p.removed) {
+            alert('Fingerprint gelöscht — Voice-ID-Gating fällt zurück auf Fail-Open.');
+          } else {
+            alert('Es war kein Fingerprint vorhanden.');
+          }
+          refreshVoiceIdStatus();
           return;
         }
 
@@ -2607,6 +2683,17 @@
       });
     }
 
+    function refreshVoiceIdStatus() {
+      const el = document.getElementById('voice-id-status');
+      if (el) el.textContent = '⏳ Status wird abgefragt...';
+      send({ action: 'voice_id_status' });
+    }
+
+    function deleteVoiceId() {
+      if (!confirm('Voice-ID-Fingerprint loeschen?\n\nDanach muss in der App neu enrolled werden.')) return;
+      send({ action: 'voice_id_delete' });
+    }
+
     function deleteXttsVoice(name) {
       if (!confirm(`Stimme "${name}" endgueltig loeschen?`)) return;
       send({ action: 'xtts_delete_voice', name });
@@ -2823,12 +2910,15 @@
       const fluxKeywordRaw = document.getElementById('diag-flux-keyword-raw')?.value;
       const fluxKeywordSwitch = document.getElementById('diag-flux-keyword-switch')?.value;
       const huggingfaceToken = document.getElementById('diag-flux-hf-token')?.value;
+      const voiceIdThresholdRaw = document.getElementById('diag-voice-id-threshold')?.value;
+      const voiceIdThreshold = voiceIdThresholdRaw ? parseFloat(voiceIdThresholdRaw) : undefined;
       send({
         action: 'send_voice_config',
         ttsEnabled, xttsVoice, whisperModel,
         f5ttsModel, f5ttsCkptFile, f5ttsVocabFile,
         f5ttsCfgStrength, f5ttsNfeStep,
         fluxDefaultModel, fluxKeywordRaw, fluxKeywordSwitch, huggingfaceToken,
+        voiceIdThreshold,
       });
       const statusEl = document.getElementById('voice-status');
       if (statusEl && xttsVoice) {
@@ -3354,6 +3444,7 @@
         loadRuntimeConfig();
         loadOnboardingQR();
         loadOAuthServices();
+        refreshVoiceIdStatus();
       } else if (tab === 'brain') {
         loadBrainStatus();
         loadBrainMemoryList();

diagnostic/server.js

@@ -2367,6 +2367,12 @@ wss.on("connection", (ws) => {
         if (msg.huggingfaceToken !== undefined) {
           voiceConfig.huggingfaceToken = String(msg.huggingfaceToken || "").trim();
         }
+        // Voice-ID Match-Threshold (0.30-0.70). Wird von der whisper-bridge
+        // ueber den config-Broadcast aufgenommen — Phase 3 nutzt's beim Gating.
+        if (msg.voiceIdThreshold !== undefined && !isNaN(msg.voiceIdThreshold)) {
+          const t = parseFloat(msg.voiceIdThreshold);
+          if (t >= 0.0 && t <= 1.0) voiceConfig.voiceIdThreshold = t;
+        }
         try {
           fs.mkdirSync("/shared/config", { recursive: true });
           fs.writeFileSync("/shared/config/voice_config.json", JSON.stringify(voiceConfig, null, 2));
@@ -2390,6 +2396,15 @@ wss.on("connection", (ws) => {
         handleGetModel(ws);
       } else if (msg.action === "set_model") {
         handleSetModel(ws, msg.model);
+      } else if (msg.action === "voice_id_status") {
+        // An whisper-bridge weiterleiten + Antwort an Browser zurueck
+        const reqId = `vid_${Date.now().toString(36)}`;
+        sendToRVS_withResponse("voice_id_status_request", { requestId: reqId },
+                               "voice_id_status_response", ws);
+      } else if (msg.action === "voice_id_delete") {
+        const reqId = `viddel_${Date.now().toString(36)}`;
+        sendToRVS_withResponse("voice_id_delete_request", { requestId: reqId },
+                               "voice_id_delete_response", ws);
       }
       // get_openclaw_config entfernt — aria-core ist raus.
     } catch {}

rvs/server.js

@@ -42,6 +42,12 @@ const ALLOWED_TYPES = new Set([
   // die feuert stt_endpoint mit dem finalen Text — kein Audio-Roundtrip.
   "stt_stream_start", "stt_audio_chunk", "stt_stream_end",
   "stt_partial", "stt_endpoint", "stt_stream_done",
+  // Speaker-ID / Voice-Enrollment (Phase 1+2): App schickt 5-10 Samples zur
+  // whisper-bridge, die berechnet einen Voice-Fingerprint (Embedding-Vektor)
+  // und nutzt ihn um nur Stefans Stimme an Whisper STT durchzulassen.
+  "voice_id_status_request", "voice_id_status_response",
+  "voice_id_enroll_request", "voice_id_enroll_response",
+  "voice_id_delete_request", "voice_id_delete_response",
   // File-Versioning (Datei-Manager in App): Versionen pro Datei listen,
   // alte Versionen herunterladen, Restore = non-destructive neuer Commit.
   "file_version_list_request", "file_version_list_response",

xtts/docker-compose.yml

@@ -85,4 +85,7 @@ services:
                                                  # ein Modell muss nur einmal pro
                                                  # Maschine geladen werden, kein
                                                  # Re-Download bei Container-Restart.
+      - ./voice-id:/voice-id                     # Speaker-ID-Fingerprint (Stefans
+                                                 # Stimm-Embedding) persistent zwischen
+                                                 # Container-Restarts.
     restart: unless-stopped

xtts/whisper/Dockerfile

@@ -1,14 +1,22 @@
 FROM nvidia/cuda:12.2.2-cudnn8-runtime-ubuntu22.04
 
+ENV DEBIAN_FRONTEND=noninteractive
+ENV PYTHONUNBUFFERED=1
+
 RUN apt-get update && apt-get install -y --no-install-recommends \
-    python3 python3-pip ffmpeg \
+    python3 python3-pip ffmpeg git \
     && rm -rf /var/lib/apt/lists/*
 
 WORKDIR /app
 
+# PyTorch CUDA-Wheels zuerst (sonst zieht speechbrain CPU-only Torch rein
+# falls f5tts den Cache noch nicht geseedet hat).
+RUN pip3 install --no-cache-dir torch==2.3.1 torchaudio==2.3.1 \
+    --index-url https://download.pytorch.org/whl/cu121
+
 COPY requirements.txt .
 RUN pip3 install --no-cache-dir -r requirements.txt
 
-COPY bridge.py .
+COPY bridge.py speaker_id.py ./
 
 CMD ["python3", "bridge.py"]

xtts/whisper/bridge.py

@@ -33,6 +33,8 @@ import sys
 import tempfile
 import time
 from dataclasses import dataclass, field
+
+import speaker_id
 from typing import Optional
 
 import numpy as np
@@ -61,6 +63,7 @@ ALLOWED_MODELS = {"tiny", "base", "small", "medium", "large-v3"}
 
 # Streaming-Parameter (Defaults — koennen pro Session vom App-Payload ueberschrieben werden)
 STREAM_TRANSCRIBE_INTERVAL_MS = 700   # alle 700ms transkribieren waehrend Stream laeuft
+STREAM_SPEAKER_CHECK_MS = 1500        # Mindest-Audio fuer Speaker-ID-Pruefung
 STREAM_DEFAULT_ENDPOINT_MS = 1500     # nach 1.5s ohne neuen Text → Endpoint
 STREAM_DEFAULT_HARD_CAP_MS = 60000    # nach 60s Audio: harter Cut egal was
 STREAM_MIN_AUDIO_MS = 600             # erst transkribieren wenn min 600ms Audio da
@@ -309,6 +312,12 @@ class StreamSession:
     last_transcribe_at: float = 0.0
     closed: bool = False       # nach stream_end gesetzt
     endpoint_sent: bool = False  # Endpoint nur einmal feuern
+    # Speaker-ID Gating: bei aktiviertem Fingerprint pruefen wir die ersten
+    # ~1.5s der Aufnahme. Bei mismatch wird die Session sofort beendet mit
+    # synthetischem stt_endpoint(text='', reason='speaker_mismatch').
+    speaker_checked: bool = False
+    speaker_match: Optional[bool] = None
+    speaker_similarity: float = 0.0
 
 
 class SessionManager:
@@ -420,6 +429,77 @@ class SessionManager:
                                 sid[:8], now - sess.last_chunk_at)
                     self.drop(sid)
 
+    async def _check_speaker(self, sess: StreamSession, ws) -> None:
+        """Speaker-ID einmalig pro Session: nimmt die ersten ~1.5s Audio,
+        rechnet das Embedding, vergleicht mit dem persistierten Fingerprint.
+        Ohne Fingerprint → fail-open (match=True). Bei mismatch wird die
+        Session sofort beendet mit synthetischem stt_endpoint."""
+        sess.speaker_checked = True
+        # Erste ~1.5s aus dem Buffer entnehmen (16kHz * 2 byte/sample = 32 bytes/ms)
+        head_bytes = bytes(sess.pcm_buffer[: STREAM_SPEAKER_CHECK_MS * 32])
+        if len(head_bytes) < speaker_id.MIN_SAMPLE_BYTES:
+            # Zu wenig — durchlassen
+            sess.speaker_match = True
+            sess.speaker_similarity = 0.0
+            return
+        try:
+            loop = asyncio.get_running_loop()
+            is_match, sim = await loop.run_in_executor(
+                None, speaker_id.verify, head_bytes,
+            )
+        except Exception as exc:
+            logger.warning("Stream %s: speaker-check crashed (%s) — fail-open",
+                           sess.request_id[:8], exc)
+            sess.speaker_match = True
+            sess.speaker_similarity = 0.0
+            return
+        sess.speaker_match = is_match
+        sess.speaker_similarity = sim
+        logger.info("Stream %s: speaker-check sim=%.2f → %s (threshold=%.2f)",
+                    sess.request_id[:8], sim, "MATCH" if is_match else "REJECT",
+                    speaker_id.DEFAULT_THRESHOLD)
+        await _debug_log(ws, "speaker.check",
+            f"id={sess.request_id[:12]} sim={sim:.2f} "
+            f"thr={speaker_id.DEFAULT_THRESHOLD:.2f} "
+            f"{'MATCH' if is_match else 'REJECT'}")
+        if not is_match:
+            await self._finalize_speaker_mismatch(sess, ws, sim)
+
+    async def _finalize_speaker_mismatch(self, sess: StreamSession, ws,
+                                         similarity: float) -> None:
+        """Bei Speaker-Mismatch: synthetisches stt_endpoint (text='', reason=
+        'speaker_mismatch') schicken damit der App-Pfad sauber endet
+        (endConversation), Session droppen. Kein Whisper-Transcribe.
+        Spart die Token + die STT-Latenz fuer fremde Stimmen."""
+        if sess.endpoint_sent:
+            return
+        sess.endpoint_sent = True
+        duration_s = self._buffer_duration_ms(sess) / 1000.0
+        logger.info("Stream %s: speaker-mismatch (sim=%.2f) — DROP nach %.1fs",
+                    sess.request_id[:8], similarity, duration_s)
+        endpoint_payload = {
+            "requestId": sess.request_id,
+            "audioRequestId": sess.audio_request_id,
+            "text": "",
+            "reason": "speaker_mismatch",
+            "durationS": duration_s,
+            "sttMs": 0,
+            "voice": sess.voice,
+            "speed": sess.speed,
+            "interrupted": sess.interrupted,
+            "speakerSimilarity": float(similarity),
+        }
+        if sess.location:
+            endpoint_payload["location"] = sess.location
+        await _send(ws, "stt_endpoint", endpoint_payload)
+        await _send(ws, "stt_stream_done", {
+            "requestId": sess.request_id,
+            "audioRequestId": sess.audio_request_id,
+            "text": "",
+            "reason": "speaker_mismatch",
+        })
+        self.drop(sess.request_id)
+
     async def _tick_session(self, sess: StreamSession, now: float) -> None:
         ws = self._ws
         if ws is None:
@@ -440,6 +520,15 @@ class SessionManager:
             await self._finalize(sess, ws, reason="stream_end")
             return
 
+        # Speaker-ID Gating: sobald genug Audio da ist, einmalig pruefen ob's
+        # Stefan ist. Bei Mismatch → synthetisches Endpoint, Session zu.
+        # Wenn kein Fingerprint persistiert ist, returnt verify() fail-open
+        # mit (True, 0.0) — keine Auswirkung.
+        if not sess.speaker_checked and audio_ms >= STREAM_SPEAKER_CHECK_MS:
+            await self._check_speaker(sess, ws)
+            if sess.speaker_match is False:
+                return  # Session bereits beendet via _finalize_speaker_mismatch
+
         # Noch zu wenig Audio fuer eine erste Transkription
         if audio_ms < STREAM_MIN_AUDIO_MS:
             return
@@ -729,10 +818,67 @@ async def run_loop(runner: WhisperRunner, sessions: SessionManager) -> None:
                             f"received id={req_id[:12]} reason={payload.get('reason', '')}")
                         sessions.end_session(req_id)
 
+                    elif mtype == "voice_id_status_request":
+                        req_id = payload.get("requestId", "")
+                        try:
+                            status = speaker_id.status()
+                        except Exception as exc:
+                            await _send(ws, "voice_id_status_response", {
+                                "requestId": req_id, "ok": False, "error": str(exc)[:200],
+                            })
+                            continue
+                        await _send(ws, "voice_id_status_response", {
+                            "requestId": req_id, "ok": True, **status,
+                        })
+
+                    elif mtype == "voice_id_enroll_request":
+                        # samples: Liste von base64-kodierten int16-LE-PCM-Buffern,
+                        # 16kHz mono, je ~3-5s. App nimmt sie nacheinander auf und
+                        # schickt sie zusammen.
+                        req_id = payload.get("requestId", "")
+                        samples = payload.get("samples") or []
+                        logger.info("voice_id_enroll_request: %d Samples (id=%s)",
+                                    len(samples), req_id[:8])
+                        try:
+                            result = await asyncio.get_running_loop().run_in_executor(
+                                None, speaker_id.enroll_from_samples, samples
+                            )
+                        except Exception as exc:
+                            logger.warning("voice_id_enroll failed: %s", exc)
+                            await _send(ws, "voice_id_enroll_response", {
+                                "requestId": req_id, "ok": False, "error": str(exc)[:300],
+                            })
+                            continue
+                        await _send(ws, "voice_id_enroll_response", {
+                            "requestId": req_id, "ok": True,
+                            "sample_count": result.get("sample_count", 0),
+                            "rejected": result.get("rejected", []),
+                            "updated_at": result.get("updated_at"),
+                            "embedding_dim": result.get("embedding_dim"),
+                        })
+
+                    elif mtype == "voice_id_delete_request":
+                        req_id = payload.get("requestId", "")
+                        removed = speaker_id.delete_fingerprint()
+                        await _send(ws, "voice_id_delete_response", {
+                            "requestId": req_id, "ok": True, "removed": removed,
+                        })
+
                     elif mtype == "config":
                         # Debug-Toggle: aria-bridge broadcastet jetzt whisperDebugLog
                         # damit Stefan im laufenden Betrieb via Diagnostic-Settings
                         # die Logs an/aus schalten kann.
+                        # Voice-ID Match-Threshold (von Diagnostic gesendet) auf das
+                        # speaker_id-Modul setzen — wird erst in Phase 3 beim Gating
+                        # genutzt, aber persistiert bereits jetzt.
+                        if "voiceIdThreshold" in payload:
+                            try:
+                                t = float(payload.get("voiceIdThreshold", 0.5))
+                                if 0.0 <= t <= 1.0:
+                                    speaker_id.DEFAULT_THRESHOLD = t
+                                    logger.info("[speaker-id] threshold gesetzt: %.2f", t)
+                            except (TypeError, ValueError):
+                                pass
                         if "whisperDebugLog" in payload:
                             global _DEBUG_LOG_TO_BRIDGE
                             old = _DEBUG_LOG_TO_BRIDGE

xtts/whisper/requirements.txt

@@ -2,3 +2,6 @@ faster-whisper==1.0.3
 websockets>=12.0
 numpy>=1.24
 requests>=2.31
+# Speaker-ID via SpeechBrain ECAPA-TDNN — Stimme von Stefan zuverlaessig
+# rauskennen damit Hintergrund-Gespraeche keine Brain-Calls triggern.
+speechbrain>=1.0.0

xtts/whisper/speaker_id.py

@@ -0,0 +1,231 @@
+"""
+Speaker-ID Backend fuer ARIAs Stimmen-Erkennung.
+
+Nutzt SpeechBrain ECAPA-TDNN (192-dim Embeddings, auf VoxCeleb-1+2 trainiert).
+Fingerprint = gemittelter, L2-normalisierter Embedding-Vektor aus N
+Enrollment-Samples. Verify: cosine_similarity(neue_aufnahme, fingerprint).
+
+Persistenz: /voice-id/fingerprint.json (Float-Liste + Metadaten).
+Modell-Cache: /root/.cache/huggingface/ (Bind-Mount mit f5tts geteilt).
+
+Verhalten OHNE Enrollment (kein Fingerprint vorhanden):
+  verify() → (True, 0.0) — Fail-open, damit Speaker-ID-Gating den
+  ungeenrollten Brain-Pfad nicht versehentlich blockiert.
+"""
+
+from __future__ import annotations
+
+import base64
+import json
+import logging
+import os
+import time
+from pathlib import Path
+from typing import Optional
+
+import numpy as np
+
+logger = logging.getLogger(__name__)
+
+VOICE_ID_DIR = Path(os.environ.get("VOICE_ID_DIR", "/voice-id"))
+FINGERPRINT_FILE = VOICE_ID_DIR / "fingerprint.json"
+
+# Cosine-Threshold: 0.5 ist konservativ (wenig false-positives), 0.3 ist
+# locker (mehr Treffer auch bei Nebengeraeuschen). Stefan kann's per
+# Diagnostic-Setting feintunen.
+DEFAULT_THRESHOLD = 0.5
+
+# Minimal-Sample-Laenge fuer ein verlaessliches Embedding (~1s @ 16kHz int16 = 32000 bytes)
+MIN_SAMPLE_BYTES = 32000
+
+_model = None
+
+
+def _ensure_loaded():
+    """Lazy-Load des ECAPA-TDNN. Holt das Modell beim ersten Aufruf von HF;
+    danach cached im HF-Cache-Volume. Erste Init: ~30s download + load,
+    danach <1s warm. Wirft bei Fehler — Caller muss catchen + fail-open."""
+    global _model
+    if _model is not None:
+        return _model
+    import torch
+    from speechbrain.inference.speaker import EncoderClassifier
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    logger.info("[speaker-id] loading ECAPA-TDNN on %s ...", device)
+    _model = EncoderClassifier.from_hparams(
+        source="speechbrain/spkrec-ecapa-voxceleb",
+        savedir="/root/.cache/huggingface/speechbrain-ecapa",
+        run_opts={"device": device},
+    )
+    logger.info("[speaker-id] model ready (device=%s)", device)
+    return _model
+
+
+def _normalize_audio_bytes(audio_bytes: bytes) -> bytes:
+    """Akzeptiert entweder rohes 16kHz int16 LE PCM ODER eine WAV-Datei (RIFF/WAVE).
+    Bei WAV wird der Header gestrippt + Format validiert (16kHz / mono / int16).
+    Ergebnis: rohes PCM."""
+    if (len(audio_bytes) >= 44
+        and audio_bytes[:4] == b"RIFF"
+        and audio_bytes[8:12] == b"WAVE"):
+        import io
+        import wave
+        with wave.open(io.BytesIO(audio_bytes), "rb") as wav:
+            sr = wav.getframerate()
+            ch = wav.getnchannels()
+            sw = wav.getsampwidth()
+            if sr != 16000:
+                raise ValueError(f"WAV-Samplerate {sr} != 16000")
+            if ch != 1:
+                raise ValueError(f"WAV-Kanalzahl {ch} != 1 (mono erwartet)")
+            if sw != 2:
+                raise ValueError(f"WAV-Sampleweite {sw} != 2 (int16 erwartet)")
+            return wav.readframes(wav.getnframes())
+    return audio_bytes
+
+
+def _audio_bytes_to_tensor(audio_bytes: bytes):
+    """int16 LE PCM (16kHz mono) → Torch-Tensor (1, N), normalisiert auf [-1, 1].
+    WAV wird vorher auf rohes PCM reduziert (Header strippen)."""
+    import torch
+    raw = _normalize_audio_bytes(audio_bytes)
+    arr = np.frombuffer(raw, dtype=np.int16).astype(np.float32) / 32768.0
+    return torch.from_numpy(arr).unsqueeze(0)
+
+
+def embed(audio_bytes: bytes) -> np.ndarray:
+    """Berechnet das Speaker-Embedding fuer einen Audio-Chunk.
+    Erwartet 16kHz int16 LE PCM Mono. Returns 192-dim numpy float32."""
+    import torch
+    model = _ensure_loaded()
+    wav = _audio_bytes_to_tensor(audio_bytes)
+    with torch.no_grad():
+        emb = model.encode_batch(wav)
+    return emb.squeeze().cpu().numpy().astype(np.float32)
+
+
+def cosine_similarity(a: np.ndarray, b: np.ndarray) -> float:
+    """Kosinus-Aehnlichkeit zwischen zwei 1D-Vektoren, Range [-1, 1].
+    Hoeher = aehnlicher. Bei normalisierten Vektoren ist das gleich dem Skalarprodukt."""
+    na = np.linalg.norm(a)
+    nb = np.linalg.norm(b)
+    if na < 1e-9 or nb < 1e-9:
+        return 0.0
+    return float(np.dot(a, b) / (na * nb))
+
+
+def save_fingerprint(embeddings: list[np.ndarray], sample_durations_s: list[float]) -> dict:
+    """Mittelt + L2-normalisiert die Embeddings und schreibt sie nach
+    FINGERPRINT_FILE. Returns das gespeicherte Dict."""
+    if not embeddings:
+        raise ValueError("Keine Embeddings zum Speichern")
+    VOICE_ID_DIR.mkdir(parents=True, exist_ok=True)
+    stacked = np.stack(embeddings)
+    mean = stacked.mean(axis=0)
+    mean = mean / max(np.linalg.norm(mean), 1e-9)
+    data = {
+        "version": 1,
+        "embedding": mean.tolist(),
+        "embedding_dim": int(mean.shape[0]),
+        "sample_count": len(embeddings),
+        "sample_durations_s": [float(s) for s in sample_durations_s],
+        "updated_at": int(time.time()),
+    }
+    FINGERPRINT_FILE.write_text(json.dumps(data, indent=2), encoding="utf-8")
+    logger.info("[speaker-id] fingerprint gespeichert: %d Samples, dim=%d, total_s=%.1f",
+                len(embeddings), mean.shape[0], sum(sample_durations_s))
+    return data
+
+
+def load_fingerprint() -> Optional[dict]:
+    """Returns das Fingerprint-Dict oder None wenn noch nicht enrolled."""
+    if not FINGERPRINT_FILE.exists():
+        return None
+    try:
+        return json.loads(FINGERPRINT_FILE.read_text(encoding="utf-8"))
+    except Exception as exc:
+        logger.warning("[speaker-id] fingerprint laden fehlgeschlagen: %s", exc)
+        return None
+
+
+def delete_fingerprint() -> bool:
+    """Loescht den Fingerprint (z.B. fuer Re-Enrollment). True wenn was weg ist."""
+    if FINGERPRINT_FILE.exists():
+        FINGERPRINT_FILE.unlink()
+        logger.info("[speaker-id] fingerprint geloescht")
+        return True
+    return False
+
+
+def verify(audio_bytes: bytes, threshold: Optional[float] = None) -> tuple[bool, float]:
+    """Returns (is_match, similarity).
+
+    Wenn threshold=None: nutzt den Modul-Default (DEFAULT_THRESHOLD) — der wird
+    vom config-Broadcast zur Laufzeit auf den Diagnostic-Slider-Wert gesetzt.
+    Default-Arg-Bindung waere zur Def-Zeit, also bewusst None statt direkt.
+
+    Fail-open: wenn kein Fingerprint vorhanden ist oder das Embedding-Modell
+    crasht, returnt (True, 0.0) — kein Filtering. Sonst wuerde ein kaputter
+    Speaker-ID-Service die ganze Aufnahme blockieren."""
+    if threshold is None:
+        threshold = DEFAULT_THRESHOLD
+    fp = load_fingerprint()
+    if fp is None:
+        return True, 0.0
+    if len(audio_bytes) < MIN_SAMPLE_BYTES:
+        # Zu wenig Audio fuer ein verlaessliches Embedding → durchlassen
+        return True, 0.0
+    try:
+        saved_emb = np.array(fp["embedding"], dtype=np.float32)
+        new_emb = embed(audio_bytes)
+    except Exception as exc:
+        logger.warning("[speaker-id] verify embed failed: %s — fail-open", exc)
+        return True, 0.0
+    sim = cosine_similarity(new_emb, saved_emb)
+    return sim >= threshold, sim
+
+
+def status() -> dict:
+    """Status-Snapshot fuer die App / Diagnostic."""
+    fp = load_fingerprint()
+    return {
+        "enrolled": fp is not None,
+        "sample_count": fp.get("sample_count", 0) if fp else 0,
+        "sample_durations_s": fp.get("sample_durations_s", []) if fp else [],
+        "updated_at": fp.get("updated_at") if fp else None,
+        "embedding_dim": fp.get("embedding_dim") if fp else None,
+        "default_threshold": DEFAULT_THRESHOLD,
+    }
+
+
+def enroll_from_samples(samples_b64: list[str]) -> dict:
+    """Verarbeitet base64-Samples (16kHz int16 LE PCM Mono) zu einem neuen
+    Fingerprint. Returns Status-Dict. Wirft ValueError wenn nichts brauchbar ist."""
+    if not samples_b64:
+        raise ValueError("Keine Samples uebergeben")
+    embeddings: list[np.ndarray] = []
+    durations: list[float] = []
+    rejected: list[dict] = []
+    for idx, s in enumerate(samples_b64):
+        try:
+            raw = base64.b64decode(s)
+        except Exception as exc:
+            rejected.append({"index": idx, "reason": f"base64: {exc}"})
+            continue
+        if len(raw) < MIN_SAMPLE_BYTES:
+            rejected.append({"index": idx, "reason": f"zu kurz ({len(raw)} bytes)"})
+            continue
+        try:
+            emb = embed(raw)
+            embeddings.append(emb)
+            durations.append(len(raw) / 2 / 16000.0)
+        except Exception as exc:
+            rejected.append({"index": idx, "reason": f"embed: {exc}"})
+    if not embeddings:
+        raise ValueError(
+            f"Keine Samples konnten verarbeitet werden ({len(rejected)} rejected). "
+            f"Details: {rejected[:3]}"
+        )
+    fingerprint = save_fingerprint(embeddings, durations)
+    fingerprint["rejected"] = rejected
+    return fingerprint