feat: voice S2S — faster-whisper STT, Kokoro TTS, PTT overlay

Implements full speech-to-speech pipeline (all 4 phases):

Backend (Phase 1):
- services/stt.py: lazy WhisperModel singleton, run_in_executor transcription
- services/tts.py: lazy KPipeline singleton, WAV synthesis at 24kHz/16-bit
- routes/voice.py: /api/voice/status, /voices, /transcribe, /synthesise
- config.py: VOICE_ENABLED, STT_BACKEND, STT_MODEL, TTS_BACKEND env vars
- app.py: load STT/TTS models at startup when VOICE_ENABLED=true
- llm.py: voice_mode + voice_speech_style params inject speak-naturally prefix
- generation_task.py: voice_mode passed through from chat route
- chat.py: "voice" conversation type allowed + excluded from retention cleanup
- pyproject.toml + Dockerfile: faster-whisper, kokoro, soundfile dependencies

Frontend (Phases 2–4):
- composables/useVoiceRecorder.ts: MediaRecorder PTT wrapper
- composables/useVoiceAudio.ts: AudioContext WAV playback wrapper
- BriefingView.vue: Listen button (TTS read-aloud), auto-TTS mode, mic PTT
- VoiceOverlay.vue: global floating PTT button; creates/reuses voice conv;
  full record→transcribe→stream→TTS flow; Space bar hold-to-talk via App.vue
- SettingsView.vue: Voice tab (status badge, speech style, voice/speed)
- App.vue: mounts VoiceOverlay; Space keydown/keyup fires voice:ptt-toggle
- api/client.ts: getVoiceStatus, getVoiceList, transcribeAudio, synthesiseSpeech

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

src/fabledassistant/services/stt.py

@@ -0,0 +1,72 @@
+"""Speech-to-text service using faster-whisper (in-process, CPU/GPU)."""
+import asyncio
+import logging
+import tempfile
+import time
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from faster_whisper import WhisperModel
+
+logger = logging.getLogger(__name__)
+
+_model: "WhisperModel | None" = None
+_model_lock = asyncio.Lock()
+_load_error: str | None = None
+
+
+async def load_stt_model() -> None:
+    """Load the Whisper model. Called once at startup when VOICE_ENABLED=true."""
+    global _model, _load_error
+    from fabledassistant.config import Config
+
+    if not Config.VOICE_ENABLED:
+        return
+
+    async with _model_lock:
+        if _model is not None:
+            return
+        try:
+            from faster_whisper import WhisperModel
+
+            logger.info("Loading Whisper STT model '%s'...", Config.STT_MODEL)
+            loop = asyncio.get_running_loop()
+            _model = await loop.run_in_executor(
+                None,
+                lambda: WhisperModel(Config.STT_MODEL, device="cpu", compute_type="int8"),
+            )
+            logger.info("Whisper STT model '%s' loaded", Config.STT_MODEL)
+        except Exception:
+            _load_error = f"Failed to load Whisper model '{Config.STT_MODEL}'"
+            logger.exception(_load_error)
+
+
+def stt_available() -> bool:
+    return _model is not None
+
+
+async def transcribe(audio_bytes: bytes, mime_type: str = "audio/webm") -> str:
+    """Transcribe audio bytes to text. Runs the model in a thread executor."""
+    if _model is None:
+        raise RuntimeError("STT model not loaded")
+
+    suffix = ".webm"
+    if "ogg" in mime_type:
+        suffix = ".ogg"
+    elif "wav" in mime_type:
+        suffix = ".wav"
+    elif "mp4" in mime_type or "m4a" in mime_type:
+        suffix = ".mp4"
+
+    def _run() -> str:
+        with tempfile.NamedTemporaryFile(suffix=suffix, delete=True) as f:
+            f.write(audio_bytes)
+            f.flush()
+            t0 = time.monotonic()
+            segments, _ = _model.transcribe(f.name, beam_size=5)  # type: ignore[union-attr]
+            text = " ".join(seg.text.strip() for seg in segments).strip()
+            logger.debug("STT transcription took %.2fs", time.monotonic() - t0)
+            return text
+
+    loop = asyncio.get_running_loop()
+    return await loop.run_in_executor(None, _run)