feat: add Vosk STT - offline voice-to-text, no API key needed

README.md

@@ -58,6 +58,59 @@ User message + AI response
 | `/recall <query>` | Search memories by keyword |
 | `/forget <id>` | Delete a specific memory |
 
+### 🎤 Voice I/O (Speech-to-Text + Text-to-Speech)
+
+Fully local voice processing. No API keys, no cloud services, no costs.
+
+```
+User sends voice message
+         │
+         ▼
+  ┌──────────────┐
+  │ Download OGG │  ← Telegram Bot API
+  │ to /tmp      │
+  └──────┬───────┘
+         │
+         ▼
+  ┌──────────────┐
+  │ ffmpeg → WAV │  ← 16kHz mono (Vosk requirement)
+  │ (16kHz mono) │
+  └──────┬───────┘
+         │
+         ▼
+  ┌──────────────┐
+  │ Vosk STT     │  ← Offline, ~200ms, 68MB model
+  │ Python bridge│     Zero network calls
+  └──────┬───────┘
+         │
+         ▼
+  {"text": "...", "confidence": 0.95}
+         │
+         ▼
+  Feed into chatWithAI → AI responds
+  (optionally via TTS tool → voice reply)
+```
+
+| Component | Technology | Size | Latency | Cost |
+|---|---|---|---|---|
+| **STT** (voice→text) | [Vosk](https://alphacephei.com/vosk/) — offline speech recognition | 68MB model | ~200ms | Free |
+| **TTS** (text→voice) | [node-edge-tts](https://github.com/yayuyokit/Edge-TTS-node) — Microsoft Edge voices | No download | ~2s | Free |
+| **Audio conversion** | ffmpeg (system) | N/A | ~100ms | Free |
+
+**How it works:**
+1. Telegram sends voice as OGG Opus. Bot downloads to `/tmp`.
+2. `scripts/stt.py` — Python bridge that converts to WAV (ffmpeg) and runs Vosk inference.
+3. Returns JSON `{"text": "...", "confidence": 0.95}` to Node.js.
+4. Transcribed text enters the normal `handleTextMessage()` pipeline — full AI response with streaming, tools, memory, self-correction.
+5. AI can optionally use the `tts` tool to reply with a voice message.
+
+**Why Vosk over Whisper:**
+- **No GPU needed** — runs on CPU, ~200MB RAM (Whisper needs 1-4GB)
+- **Fast** — 200ms vs 5-10s for Whisper on CPU
+- **Tiny model** — 68MB vs 1-3GB for Whisper
+- **Offline** — zero network calls, zero API costs
+- **Good enough** — ~95% accuracy for English speech
+
 ### 🧠 Intelligence Routing
 
 The core of zCode CLI X's reliability. A unified agentic loop that handles both streaming and non-streaming through the same execution path — no more split paths that lose context or hang silently.
@@ -464,6 +517,10 @@ Z.AI API (SSE)
 | Telegram integration | ✅ Native bot + webhook + streaming | ✅ 2-way Telegram bridge | ❌ None |
 | Discord | ✅ Native bot (discord.js) | ✅ Full Discord integration | ❌ None |
 | Multi-channel delivery | ✅ Delivery hub (TG + DC + WS + log) | ✅ Cron→multi-platform | ❌ None |
+| **Voice** | | | |
+| Speech-to-Text | ✅ Vosk (offline, ~200ms, 68MB) | ⚠️ Whisper (needs GPU) | ❌ None |
+| Text-to-Speech | ✅ Edge TTS (free, 100+ voices) | ✅ node-edge-tts | ❌ None |
+| Voice→AI pipeline | ✅ Transcribe → full agentic loop | ⚠️ Separate pipeline | ❌ None |
 | **Infrastructure** | | | |
 | Model routing | ✅ Multi-provider | ✅ Multi-provider routing | ❌ Single model |
 | Context compression | ✅ Compact pipeline | ✅ lean-ctx MCP (90% savings) | ❌ None |
@@ -485,6 +542,8 @@ Z.AI API (SSE)
 - **Winston**: Structured logging
 - **WebSocket**: Real-time updates
 - **RTK**: Rust Token Killer (token optimization)
+- **Vosk**: Offline speech recognition (STT, 68MB model, no API key)
+- **ffmpeg**: Audio conversion (OGG → WAV for Vosk)
 
 ## 🤝 Contributing