Unmute-style voice stack (documentation card)
This repository is a documentation-only model card. It describes an Unmute-style STT → LLM → TTS voice stack for portfolio and architecture context. It does not host a runnable Unmute deployment, GPU inference, or model weights.
What this card is
A concise architecture note for a low-latency conversational voice pipeline patterned after
Kyutai Unmute: speech in, text reasoning, speech out.
What this card is not
- Not a GPU Unmute host — no backend, STT, TTS, or LLM servers run from this repo.
- Not a redistribution of Kyutai weights — STT/TTS checkpoints remain upstream; obtain them from Kyutai / Hugging Face under their terms.
- Not a deploy package — no Docker Compose, RunPod configs, API keys, tokens, private hostnames, or
.env files.
- Not a claim of plant-grade voice control — see Claim boundary.
Pipeline (STT → LLM → TTS)
On a high level:
1User audio
2 → Speech-to-text (Kyutai STT)
3 → Text LLM (any OpenAI-compatible text model)
4 → Text-to-speech (Kyutai TTS)
5 → Spoken reply
- STT — A low-latency speech-to-text model (Kyutai STT family) streams partial transcripts while the user speaks.
- LLM — When turn-taking decides a response is due, a text LLM generates the reply. Unmute is designed to wrap any text LLM (local vLLM, hosted OpenAI-compatible APIs, etc.).
- TTS — As tokens arrive, Kyutai TTS synthesizes audio and streams it back to the client.
Unmute-style systems typically put a thin backend between a browser (or other client) and these three services, often over WebSockets, so audio and metadata can flow in real time.
1graph LR
2 Client[Client] --> Backend[Backend]
3 Backend --> STT[Speech-to-text]
4 Backend --> LLM[Text LLM]
5 Backend --> TTS[Text-to-speech]
Upstream references
All architecture narrative here is derived from publicly documented Unmute / Kyutai materials. Weights, licenses, and gated-model access are governed by the upstream projects—not by this card.
Relevance to industrial multimodal interfaces
Voice is a natural modality near operations work: hands-busy operators, field technicians, and control-room side channels often need spoken Q&A or status readback without replacing existing HMI/SCADA.
An Unmute-style stack is relevant as a research and interface pattern for:
- multimodal operator assistants that combine speech with text/vision context;
- low-latency conversational UX experiments adjacent to industrial software;
- separating perception (STT), reasoning (text LLM), and rendering (TTS) so each tier can be swapped or hosted independently.
This card does not claim that such a stack is certified, safety-rated, or wired into any plant control path.
Claim boundary
| Claim | Status |
|---|
| Documents an Unmute-style STT → LLM → TTS architecture | Yes |
| Points to public upstream demos, code, and paper | Yes |
| Hosts or serves Kyutai / Unmute model weights | No |
| Provides a running GPU Unmute or voice inference endpoint | No |
| Includes deploy secrets, private endpoints, or RunPod configs | No |
| Asserts real-plant savings, safety integrity, or control authority | No |
| Asserts SOTA ASR/TTS/LLM benchmarks from this repo | No |
Treat this artifact as portfolio documentation for a Vision · Voice · Language collection—architecture literacy, not a product release.
License note
This documentation card is offered under Apache-2.0. Upstream Unmute, Kyutai models, papers, and third-party LLMs retain their own licenses and terms.
