jamiepine/voicebox

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The open-source AI voice studio. Clone, dictate, create. 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 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