# Local speech platform VoiceStudio is both a desktop dictation app and a headless local speech service. The desktop app owns microphone capture, the dictation shortcut and native insertion; the Python backend keeps ASR models warm and exposes the audio data plane to any other interface. ```text VS Code / custom GUI / remote mic ── PCM or WebM ───────> WS/HTTP :3900 │ └─ partial/final text Scripts / TUIs / hooks ── audio files ──────────────────> HTTP :3900 Claude Code / Codex / Pi / agents ── MCP HTTP/stdio ───> MCP :3900 ``` > **Native dictation control is retired.** The Tauri desktop app bundled a > loopback control server on port 3902 (`/v1/dictation/*`, JSON-RPC, > `--dictate-*` flags, output sessions). The Electron app does not provide it, > and 3902 is now its development server's port. Use the in-app dictation > shortcut, or capture audio yourself and stream it as described below. ## Discover capabilities ```bash curl http://127.0.0.1:3900/.well-known/voicestudio-speech ``` The document returns `voicestudio.speech.v1` with relative URLs, so it also works behind Tailscale or a reverse proxy. `features.native_dictation_control` remains in the schema and is always `false`. The dependency-free Python bridge is convenient for hooks and TUIs: ```bash python -m backend.speech_client capabilities python -m backend.speech_client transcribe recording.wav ``` It targets `VOICESTUDIO_URL`, else the loopback backend on `OMNIVOICE_PORT` (default 3900), and sends `OMNIVOICE_API_KEY` as a bearer key when set. The former `status`, `start`, `stop`, `toggle` and `transcribe --insert` commands exit with an explanation. ## Bring your own capture interface An editor extension or GUI can own the microphone and consume live text. Connect to: ```text ws://127.0.0.1:3900/v1/audio/transcriptions/stream ``` Send binary WebM/Opus frames by default. For raw signed 16-bit mono PCM, use `?pcm=1&sr=16000`. Finish without closing the socket by sending: ```json {"type":"input_audio.end"} ``` Every response carries `protocol` and `session_id`: ```json {"type":"session.started","protocol":"voicestudio.speech.v1","session_id":"..."} {"type":"partial","text":"hello wor...","session_id":"..."} {"type":"final","final_kind":"summary","text":"Hello world.","session_id":"..."} ``` Streaming Sherpa models can also emit `final_kind: "utterance"` before the authoritative whole-session `summary`. Existing `/ws/transcribe` clients keep their unchanged legacy frames and `EOF` control. ## Batch and agent protocols | Transport | Endpoint | Use | |---|---|---| | OpenAI-compatible HTTP | `POST :3900/v1/audio/transcriptions` | Files, scripts, existing SDKs | | WebSocket | `:3900/v1/audio/transcriptions/stream` | Partial and final live text | | MCP Streamable HTTP | `POST :3900/mcp/` (bare `/mcp` on current backends) | Modern agent clients | | MCP stdio | `python -m backend.mcp_shim` | Claude Code, Codex, and stdio-only clients | ## Integration map | Interface | Recommended connection | |---|---| | Any desktop text field | The app's global dictation shortcut | | Pi, Claude Code, Codex, Antigravity CLI | Dictate into the focused prompt with the shortcut; add MCP when the agent also needs file transcription or speech tools | | VS Code | Stream editor-owned mic audio over the versioned WebSocket | | TUI or shell script | `python -m backend.speech_client` or the OpenAI-compatible HTTP endpoint | | Browser/WebView UI | Stream audio to the Python data plane | | Remote microphone + local/remote GPU | Capture at the client edge and use the authenticated WebSocket/OpenAI endpoint | Loopback clients need no credential. Remote native WebSocket clients can send the configured bearer key. Browser clients should exchange that key for a short-lived session, mint a path-bound ticket at `/api/auth/ws-ticket`, and connect with `?ws_ticket=...`; see [API authentication](api-auth.md). Keep remote endpoints restricted to a trusted network; an API key authenticates a client but does not provide network isolation. Beyond a fully trusted LAN, use HTTPS/WSS and never send bearer credentials or ticket exchanges over plaintext HTTP/WebSocket. ## Security and privacy - No interface can turn on the desktop app's microphone remotely; capture starts only from the app itself. Remote ASR stays on the existing API-key boundary. - Microphones stay at the interface edge. A remote GPU backend never assumes it owns the user's input device. - No protocol adds a required network call, account, analytics event, or cloud provider. ## Research basis The design survey covered five pages of GitHub's [`speech-to-text` topic](https://github.com/topics/speech-to-text): [1](https://github.com/topics/speech-to-text?page=1), [2](https://github.com/topics/speech-to-text?page=2), [3](https://github.com/topics/speech-to-text?page=3), [4](https://github.com/topics/speech-to-text?page=4), and [5](https://github.com/topics/speech-to-text?page=5). The platform keeps the strongest reusable ideas without copying their UI boundaries: | Source | Adopted idea | |---|---| | [Handy](https://github.com/cjpais/Handy) | Cross-platform offline dictation, external toggle control, VAD-oriented capture | | [WhisperLiveKit](https://github.com/QuentinFuxa/WhisperLiveKit) | Live local transcription and compatibility-oriented serving | | [RealtimeSTT](https://github.com/KoljaB/RealtimeSTT) | Low-latency partials, endpointing, and warm recognizers | | [sherpa-onnx](https://github.com/k2-fsa/sherpa-onnx) | Portable CPU streaming models and WebSocket-friendly audio framing | | [FunASR](https://github.com/modelscope/FunASR) | OpenAI-compatible and MCP-facing serving | | [Vexa](https://github.com/Vexa-ai/vexa) | WebSocket transcripts plus agent access | | [Voquill](https://github.com/voquill/voquill) | Provider independence, refinement, and personal-vocabulary direction | | [Muesli](https://github.com/Muesli-HQ/muesli) | Machine-readable CLI contracts and session-safe automation | | [Herdr](https://github.com/motionharvest/herdr) | One local control surface behind CLI, socket, hooks, and plugin integrations | The differentiator is the connection layer: one bundled app offers native capture and insertion plus a protocol-neutral ASR service, so every interface does not rebuild model loading.