voicebox

Mon, 22 Jun 2026 21:00:58 +0800

jamiepine/voicebox

Voicebox

The open-source AI voice studio.
Clone any voice. Generate speech. Dictate into any app. Talk to agents in voices you own.
The full voice I/O stack, running locally on your machine.

voicebox.sh • Docs • Download • Features • API • Troubleshooting

Click the image above to watch the demo video on voicebox.sh

What is Voicebox?

Voicebox is a local-first AI voice studio — a free and open-source alternative to ElevenLabs and WisprFlow in one app. Clone voices from a few seconds of audio, generate speech in 23 languages across 7 TTS engines, dictate into any text field with a global hotkey, and give any MCP-aware AI agent a voice of your choosing.

The two cloud incumbents sit on opposite halves of the voice I/O loop — ElevenLabs on output, WisprFlow on input. Voicebox does both, bridges them with a bundled local LLM for refinement and per-profile personas, and runs the whole thing on your machine.

Complete privacy — models, voice data, and captures never leave your machine
7 TTS engines — Qwen3-TTS, Qwen CustomVoice, LuxTTS, Chatterbox Multilingual, Chatterbox Turbo, HumeAI TADA, and Kokoro
Voice cloning and preset voices — zero-shot cloning from a reference sample, or 50+ curated preset voices via Kokoro and Qwen CustomVoice
23 languages — from English to Arabic, Japanese, Hindi, Swahili, and more
Post-processing effects — pitch shift, reverb, delay, chorus, compression, and filters
Expressive speech — paralinguistic tags like [laugh], [sigh], [gasp] via Chatterbox Turbo; natural-language delivery control via Qwen CustomVoice
Unlimited length — auto-chunking with crossfade for scripts, articles, and chapters
Stories editor — multi-track timeline for conversations, podcasts, and narratives
Voice input — global dictation hotkey with push-to-talk and toggle modes, accessibility-verified auto-paste on macOS, in-app mic on every text field, Whisper-based STT
Agent voice output — one tool call (voicebox.speak) and any MCP-aware agent (Claude Code, Cursor, Cline) speaks to you in a voice you’ve cloned
Voice personalities — attach a free-form persona to any voice profile, then Compose, Rewrite, or Respond via a bundled local LLM — agents can invoke the same modes over MCP
API-first — REST API plus a built-in MCP server for integrating voice I/O into your own apps and agents
Native performance — built with Tauri (Rust), not Electron
Runs everywhere — macOS (MLX/Metal), Windows (CUDA), Linux, AMD ROCm, Intel Arc, Docker

Download

Platform	Download
macOS (Apple Silicon)	Download DMG
macOS (Intel)	Download DMG
Windows	Download MSI
Docker	`docker compose up`

View all binaries →

Linux — Pre-built binaries are not yet available. See voicebox.sh/linux-install for build-from-source instructions.

Having trouble? See the Troubleshooting Guide for common install, generation, model-download, and GPU issues.

Features

Multi-Engine Voice Cloning

Seven TTS engines with different strengths, switchable per-generation:

Engine	Languages	Strengths
Qwen3-TTS (0.6B / 1.7B)	10	High-quality multilingual cloning, delivery instructions (“speak slowly”, “whisper”)
Qwen CustomVoice	10	9 curated preset voices with natural-language delivery control — no reference audio required
LuxTTS	English	Lightweight (~1GB VRAM), 48kHz output, 150x realtime on CPU
Chatterbox Multilingual	23	Broadest language coverage — Arabic, Danish, Finnish, Greek, Hebrew, Hindi, Malay, Norwegian, Polish, Swahili, Swedish, Turkish and more
Chatterbox Turbo	English	Fast 350M model with paralinguistic emotion/sound tags
TADA (1B / 3B)	10	HumeAI speech-language model — 700s+ coherent audio, text-acoustic dual alignment
Kokoro	8	50 curated preset voices, tiny 82M model, fast CPU inference

Emotions & Paralinguistic Tags

Only Chatterbox Turbo interprets paralinguistic tags like [laugh] and [sigh]. Qwen3-TTS, LuxTTS, Chatterbox Multilingual, and HumeAI TADA read them literally as text.

With Chatterbox Turbo selected, type / in the text input to open the tag inserter and add expressive tags inline with speech:

[laugh] [chuckle] [gasp] [cough] [sigh] [groan] [sniff] [shush] [clear throat]

Post-Processing Effects

8 audio effects powered by Spotify’s pedalboard library. Apply after generation, preview in real time, build reusable presets.

Effect	Description
Pitch Shift	Up or down by up to 12 semitones
Reverb	Configurable room size, damping, wet/dry mix
Delay	Echo with adjustable time, feedback, and mix
Chorus / Flanger	Modulated delay for metallic or lush textures
Compressor	Dynamic range compression
Gain	Volume adjustment (-40 to +40 dB)
High-Pass Filter	Remove low frequencies
Low-Pass Filter	Remove high frequencies

Ships with 4 built-in presets (Robotic, Radio, Echo Chamber, Deep Voice) and supports custom presets. Effects can be assigned per-profile as defaults.

Unlimited Generation Length

Text is automatically split at sentence boundaries and each chunk is generated independently, then crossfaded together. Works with all engines.

Configurable auto-chunking limit (100–5,000 chars)
Crossfade slider (0–200ms) for smooth transitions
Max text length: 50,000 characters
Smart splitting respects abbreviations, CJK punctuation, and [tags]

Generation Versions

Every generation supports multiple versions with provenance tracking:

Original — clean TTS output, always preserved
Effects versions — apply different effects chains from any source version
Takes — regenerate with a new seed for variation
Source tracking — each version records its lineage
Favorites — star generations for quick access

Async Generation Queue

Generation is non-blocking. Submit and immediately start typing the next one.

Serial execution queue prevents GPU contention
Real-time SSE status streaming
Failed generations can be retried
Stale generations from crashes auto-recover on startup

Voice Profile Management

Create profiles from audio files or record directly in-app
Import/export profiles to share or back up
Multi-sample support for higher quality cloning
Per-profile default effects chains
Organize with descriptions and language tags

Stories Editor

Multi-voice timeline editor for conversations, podcasts, and narratives.

Multi-track composition with drag-and-drop
Inline audio trimming and splitting
Auto-playback with synchronized playhead
Version pinning per track clip

Global Dictation & Voice Input

The other half of the voice I/O loop. Hold a hotkey anywhere on your system, speak, release — on macOS the transcript pastes straight into the focused text field. Or hit the mic on any Voicebox text input and dictate directly into the app.

Configurable chord bindings — hold-to-speak and tap-to-toggle chords, each rebindable in the in-app chord picker. Holding push-to-talk and tapping Space mid-hold upgrades into a toggle session without a gap in audio
Target-aware paste (macOS) — accessibility-verified injection into the focused text field, with atomic clipboard save/restore so your clipboard isn’t clobbered
First-run permissions UX — in-app gates walk you through the macOS Accessibility and Input Monitoring grants with deep-links to System Settings
In-app mic button on every Voicebox text field — generation form, profile descriptions, story titles, anywhere you’d type
LLM refinement — optional cleanup of ums, stutters, and false starts before paste
On-screen pill — floating overlay surfacing recording, transcribing, refining, and speaking states. Same pill agents use when they speak to you, so there’s one mental model for both directions of the loop

Speech-to-Text

Voicebox runs OpenAI Whisper for transcription — the same model that backs dictation, the Captures tab, and the /transcribe API. Running on MLX (Apple Silicon) or PyTorch (CUDA / ROCm / DirectML / CPU) depending on your platform.

Size	Notes
Base / Small / Medium / Large	Standard Whisper quality ladder
Turbo	~8x faster than Whisper Large, minimal quality loss

More engines (Parakeet v3, Qwen3-ASR) are planned — see Roadmap.

Captures

Every dictation, in-app recording, and uploaded audio file lands in the Captures tab — original audio paired with transcript, always preserved.

Replay, re-transcribe, refine — rerun STT with any Whisper size, or re-run the raw transcript through the local LLM with different flags (filler cleanup, self-correction removal, technical-term preservation)
Edit inline — tweak the transcript and save on blur
Play as voice profile — turn any capture into speech with a cloned voice, one click
Promote to voice sample — use a capture’s audio + transcript as a reference sample on any voice profile
Local capture storage — original audio and transcript stay in your Voicebox data directory, with a folder shortcut in Settings

Agent Voice Output

Every agent gets a voice. One tool call and any MCP-aware agent can speak to you in a voice you’ve cloned — task completions, questions, notifications. The same pill that surfaces during dictation surfaces during agent speech, so you always see what’s coming out of your machine.

// In any MCP-aware agent:
await voicebox.speak({
  text: "Deploy complete.",
  profile: "Morgan",
});

Also exposed as POST /speak for anything that doesn’t speak MCP — ACP, A2A, shell scripts, custom harnesses.

Bidirectional pill — recording, transcribing, refining, and speaking are all states of the same OS-level overlay, so dictation and agent speech share one surface
Per-agent voice binding — in Settings → MCP, pin Claude Code to Morgan and Cursor to Scarlett so you can tell which agent is talking without looking. Each client’s last_seen_at timestamp confirms the install actually took
Always visible — no silent background TTS; every agent-initiated speak surfaces the pill with the voice profile name for the full duration
HTTP + stdio transports — install as a URL in Claude Code / Cursor / Windsurf / VS Code MCP, or point stdio-only clients at the bundled voicebox-mcp binary

Voice Personalities

Attach a free-form personality to any voice profile — who this voice is, how they speak, what they care about. Two actions appear on the generate box when a personality is set, powered by a bundled Qwen3 LLM running entirely locally.

Compose — a shuffle button that drops a fresh in-character line into the textarea; edit and speak, or click again for a different take
Speak in character — a toggle that routes your input text through the personality LLM to be rewritten in their voice before TTS

Agents can reach the same rewrite path over MCP by passing personality: true to voicebox.speak, turning the tool into a text-in → personality-LLM → TTS pipeline. The same LLM backs dictation’s refinement step — one LLM in the app, one model cache, one GPU-memory footprint.

Local LLM options: Qwen3 0.6B / 1.7B / 4B, sharing the TTS runtime (MLX on Apple Silicon, PyTorch elsewhere).

Use cases: agent dev loops (dictate a question, hear the answer in a cloned voice), interactive characters for games and narrative tools, speech assistance for people who can’t speak in their original voice.

Model Management

Per-model unload to free GPU memory without deleting downloads
Custom models directory via VOICEBOX_MODELS_DIR
Model folder migration with progress tracking
Download cancel/clear UI

GPU Support

Platform	Backend	Notes
macOS (Apple Silicon)	MLX (Metal)	4-5x faster via Neural Engine
Windows / Linux (NVIDIA)	PyTorch (CUDA)	Auto-downloads CUDA binary from within the app
Linux (AMD)	PyTorch (ROCm)	Auto-configures HSA_OVERRIDE_GFX_VERSION
Windows (any GPU)	DirectML	Universal Windows GPU support
Intel Arc	IPEX/XPU	Intel discrete GPU acceleration
Any	CPU	Works everywhere, just slower

API

Voicebox exposes a REST API for integrating voice I/O into your own apps and agents.

# Generate speech
curl -X POST http://127.0.0.1:17493/generate \
  -H "Content-Type: application/json" \
  -d '{"text": "Hello world", "profile_id": "abc123", "language": "en"}'

# Agent voice output — any app or script can speak in a cloned voice
curl -X POST http://127.0.0.1:17493/speak \
  -H "Content-Type: application/json" \
  -H "X-Voicebox-Client-Id: my-script" \
  -d '{"text": "Deploy complete.", "profile": "Morgan"}'

# Transcribe an audio file
curl -X POST http://127.0.0.1:17493/transcribe \
  -F "audio=@recording.wav" \
  -F "model=whisper-turbo"

# List voice profiles
curl http://127.0.0.1:17493/profiles

POST /speak accepts profile as a name (case-insensitive) or id, and resolves via the same precedence as the MCP tool: explicit arg → per-client binding → capture_settings.default_playback_voice_id.

MCP server

Voicebox ships a built-in Model Context Protocol server so any MCP-aware agent (Claude Code, Cursor, Windsurf, Cline, VS Code MCP extensions) can speak, transcribe, and browse captures and profiles.

Claude Code one-liner:

claude mcp add voicebox \
  --transport http \
  --url http://127.0.0.1:17493/mcp \
  --header "X-Voicebox-Client-Id: claude-code"

Any HTTP MCP client (Cursor, Windsurf, VS Code, etc.):

{
  "mcpServers": {
    "voicebox": {
      "url": "http://127.0.0.1:17493/mcp",
      "headers": { "X-Voicebox-Client-Id": "cursor" }
    }
  }
}

Stdio fallback for clients that don’t speak HTTP MCP — point at the bundled voicebox-mcp binary inside the app:

{
  "mcpServers": {
    "voicebox": {
      "command": "/Applications/Voicebox.app/Contents/MacOS/voicebox-mcp",
      "env": { "VOICEBOX_CLIENT_ID": "claude-desktop" }
    }
  }
}

Four tools ship: voicebox.speak, voicebox.transcribe, voicebox.list_captures, voicebox.list_profiles. Per-client voice bindings are managed in Voicebox → Settings → MCP. See the full MCP guide for tool signatures, resolution precedence, the speaking-pill contract, and security notes.

// In any MCP-aware agent:
await voicebox.speak({
  text: "Tests passing. Ready to merge.",
  profile: "Morgan",      // optional — falls back to the per-client binding
  personality: true,      // optional — rewrites text through the profile's personality LLM first
});

Use cases: agent dev loops (voice in, voice out), game dialogue, podcast production, accessibility tools, voice assistants, content automation.

Full API documentation available at http://127.0.0.1:17493/docs.

Tech Stack

Layer	Technology
Desktop App	Tauri (Rust)
Frontend	React, TypeScript, Tailwind CSS
State	Zustand, React Query
Backend	FastAPI (Python)
TTS Engines	Qwen3-TTS, Qwen CustomVoice, LuxTTS, Chatterbox, Chatterbox Turbo, TADA, Kokoro
STT	Whisper / Whisper Turbo (PyTorch or MLX)
Local LLM	Qwen3 (0.6B / 1.7B / 4B), shared runtime with TTS / STT
MCP Server	FastMCP mounted at `/mcp` (Streamable HTTP) + bundled stdio shim binary
Native Shim	Rust (inside Tauri) for global hotkey, paste injection, focus introspection
Effects	Pedalboard (Spotify)
Inference	MLX (Apple Silicon) / PyTorch (CUDA/ROCm/XPU/CPU)
Database	SQLite
Audio	WaveSurfer.js, librosa

Roadmap

Feature	Description
Windows / Linux auto-paste	Dictation paste parity — `SendInput` on Windows, `uinput` / AT-SPI on Linux
STT engine expansion	Parakeet v3 and Qwen3-ASR joining Whisper — 50+ languages, better non-English quality
Pipeline routing	Configurable source → transform → sink chains with webhook + MCP sinks and a preset editor
Streaming transcription	WebSocket `/transcribe/stream` for partial transcripts as you speak
End-to-end speech LLMs	Moshi, GLM-4-Voice, Qwen2.5 Omni — real voice-to-voice, no text between
Voice Design	Create new voices from text descriptions
Long-form capture	Dual-stream recorder (mic + system audio) with summary LLM transform
Platform sinks	Apple Notes, Obsidian, and other opt-in integrations
Plugin architecture	Extend with custom models, transforms, and sinks
Mobile companion	Control Voicebox from your phone

For the full engineering status, open-issue triage, and prioritized work queue, see docs/PROJECT_STATUS.md — a living document that tracks what’s shipped, what’s in-flight, candidate TTS engines under evaluation, and why we’ve accepted or backlogged specific integrations.

Development

See CONTRIBUTING.md for detailed setup and contribution guidelines.

Quick Start

git clone https://github.com/jamiepine/voicebox.git
cd voicebox

just setup   # creates Python venv, installs all deps
just dev     # starts backend + desktop app

Install just: brew install just or cargo install just. Run just --list to see all commands.

Prerequisites: Bun, Rust, Python 3.11+, Tauri Prerequisites, and Xcode on macOS.

The repo ships a pre-wired .mcp.json at the root — running Claude Code inside this checkout picks up the Voicebox MCP tools automatically once the dev app is running.

Building Locally

1
2

just build          # Build CPU server binary + Tauri app
just build-local    # (Windows) Build CPU + CUDA server binaries + Tauri app

Adding New Voice Models

The multi-engine architecture makes adding new TTS engines straightforward. A step-by-step guide covers the full process: dependency research, backend protocol implementation, frontend wiring, and PyInstaller bundling.

The guide is optimized for AI coding agents. An agent skill can pick up a model name and handle the entire integration autonomously — you just test the build locally.

Project Structure

voicebox/
├── app/              # Shared React frontend
├── tauri/            # Desktop app (Tauri + Rust)
├── web/              # Web deployment
├── backend/          # Python FastAPI server
├── landing/          # Marketing website
└── scripts/          # Build & release scripts

Contributing

Contributions welcome! See CONTRIBUTING.md for guidelines.

Fork the repo
Create a feature branch
Make your changes
Submit a PR

Security

Found a security vulnerability? Please report it responsibly. See SECURITY.md for details.

License

MIT License — see LICENSE for details.

voicebox.sh

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