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

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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.

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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 (NVIDIA) | PyTorch (CUDA) | Auto-downloads CUDA binary from within the app | | Linux (NVIDIA) | PyTorch (CUDA) | Use a local/remote Python backend with CUDA PyTorch | | 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 |

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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.

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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 |

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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.

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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

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 integra