OmniVoice Studio

The open-source ElevenLabs alternative.

Real-time dictation, zero-shot voice cloning, and cinematic video dubbing — all on your desktop.
No accounts. No API keys. No cloud. Everything runs on your machine. Open-source, 646 languages.

Quickstart · Features · Why OVS · Engines · API · Donate · Contributing · Discord · 简体中文

Your voice is the most personal data you have. So why rent it back from a cloud? Every mainstream voice tool ships your audio to someone else's server and bills you monthly for the privilege. OmniVoice Studio flips that: clone, design, dub, and dictate on your own hardware — 646 languages, no meter running, nothing leaving your machine.

[!WARNING] Active beta. Things may break between releases — for the newest fixes, run from source. Bug reports and PRs are very welcome: open an issue or join Discord.

📸 See it in action

Studio _{Generate & clone in one workspace — a 3-second clip mirrors any voice, 646 languages, zero-shot.}	Voice Design _{Build new voices from scratch — gender, age, accent, pitch, emotion, dialect.}
Voice Gallery _{Browse ready-made archetype voices with language filters — or build your own library.}	Video Dubbing _{A real dub, end to end: 37 segments transcribed, translated to Bengali, re-voiced, and timed — ready to export as MP4.}
Settings → Engines _{The engine compatibility matrix — 14 TTS engines with per-engine GPU preflight, no silent CPU fallback.}	Settings → Models _{One-click model store — auto-detects your platform (CUDA / MPS / CPU) and recommends the right models.}

✨ Features

The eight headliners — and twelve more waiting under the fold.

🎙️ Voice Cloning

3-second clip → mirror any voice.
646 languages, zero-shot.

🎨 Voice Design

Gender, age, accent, pitch, speed,
emotion, dialect — dial it in.

🎬 Video Dubbing

YouTube URL or file → transcribe →
translate → re-voice → MP4.

📖 Audiobook Editor

Import text, EPUB, or PDF. Auto-chapter,
loudnorm, metadata. Export .m4b.

🎭 Stories

Multi-voice editor. Assign voices
per-line, preview, export full cast.

⌘+⇧+Space from any app.
Transcribes, auto-pastes, disappears.

🔐 100% Local

No keys, no cloud, no accounts.
Your machine only.

🤖 MCP Server

Use OmniVoice from Claude,
Cursor, or any MCP client.

…and 12 more — isolation, diarization, batch, watermarking, diagnostics, and friends

🔊 Vocal Isolation — Demucs-powered: splits speech from music and keeps the background bed.
👥 Speaker Diarization — Pyannote + WhisperX auto-identify who said what.
📦 Batch Queue — drop 50 videos, walk away; per-job progress bars.
🛡️ AI Watermark — AudioSeal (Meta): invisible, survives compression.
🔬 Diagnostics — self-check suite, error journal, scrubbed diagnostic bundles.
⚡ GPU Auto-Detect — CUDA · MPS · ROCm (Linux, opt-in) · CPU; ≤8 GB VRAM auto-offloads.
🧭 Engine routing — preflight GPU check per engine; no silent CPU fallback.
🧩 Extensible — subclass TTSBackend, add any engine in ~50 lines.
🎒 Portable personas — export voices as .ovsvoice bundles: identity + watermark.
♾️ Unlimited TTS — sentence-chunked generation, no length cap, streaming via WebSocket.
🌐 Remote backend — point the UI at a remote server; Tailscale-friendly, bearer auth.
🧠 Dictation + LLM — local-LLM cleanup of transcripts, optional echo cancellation.

⚡ Quickstart

_{macOS: first launch needs a one-time approval — right-click → Open (or System Settings → Privacy & Security → "Open Anyway" on macOS 15). No Terminal needed. Why? · Intel Macs: local backend unsupported (#889) — details.}

Pick your OS and follow the guide end-to-end:

🍎 macOS — docs/install/macos.md
🪟 Windows — docs/install/windows.md
🐧 Linux — docs/install/linux.md
🐳 Docker — docs/install/docker.md · Docker Hub: palashdeb/omnivoice-studio

Feels slow? docs/performance.md covers where generation time actually goes, the tuning knobs, and the three classic causes of "it got slow".

Coming from CorentinJ/Real-Time-Voice-Cloning (now archived)? There's a dedicated migration guide: docs/migration/real-time-voice-cloning.md.

🧰 Stuck? Self-checks, tokens & restricted networks

Run the built-in self-check first — Settings → About → "Run self-check" in the app, or uv run python backend/main.py --diagnose from a checkout (--deep also test-loads the active engine). Then see docs/install/troubleshooting.md for the top 10 install errors. The in-app error UI deeplinks to those entries when something breaks at runtime, and Settings → About → "Save diagnostic bundle" packages scrubbed logs + the self-check report for bug reports.

For Hugging Face token setup, see docs/setup/huggingface-token.md. For diarization-specific gating, see docs/features/diarization.md. For download speed, the ⚡ fast-download (Xet) status, and restricted-network / mirror options, see docs/downloading-models.md.

💡 Why OmniVoice?

ElevenLabs charges $5–$330/mo and processes your audio on their servers. OmniVoice Studio runs on your hardware, with no usage limits.

	ElevenLabs	OmniVoice Studio
Pricing	$5–$330/mo, per-character billing	Free & open-source (AGPL-3.0) · Commercial license for proprietary use
Voice Cloning	✅ 3s clip	✅ 3s clip, zero-shot
Voice Design	✅ Gender, age	✅ Gender, age, accent, pitch, style, dialect
Audiobook / Stories	❌	✅ Full audiobook editor + multi-voice stories (EPUB/PDF import, .m4b export)
Languages	32	646
Video Dubbing	✅ Cloud-only	✅ Fully local
Data Privacy	Audio sent to cloud	Nothing leaves your machine
API Keys	Required	Not needed
GPU Support	N/A (cloud)	CUDA · Apple Silicon · ROCm (Linux) · CPU
Desktop App	❌	✅ macOS · Windows · Linux
TTS Engines	1	14 — full matrix
ASR Engines	1	10 — full lineup
MCP Server	❌	✅ Use from Claude, Cursor, any MCP client
Self-check	❌	✅ Diagnostics suite, error journal, scrubbed debug bundles
Customizable	❌ Closed	✅ Fork it, extend it, ship it

Professional-grade voice AI, minus the subscription and the cloud.

Convinced? Come build with us.

🖥️ System Requirements

	Minimum	Recommended
OS	Windows 10, macOS 12+ (Apple Silicon), Ubuntu 24.04+ (glibc 2.39+)	Any modern 64-bit OS
RAM	8 GB	16 GB+
VRAM (GPU)	4 GB (auto-offloads TTS to CPU)	8 GB+ (NVIDIA RTX 3060+)
Disk	10 GB free (models + cache)	20 GB+ SSD
Python	3.10+ (managed by `uv`)	3.11–3.12
GPU	Optional — CPU works	NVIDIA CUDA · Apple Silicon MPS · AMD ROCm (Linux only)

[!TIP] On GPUs with ≤8 GB VRAM, OmniVoice automatically offloads TTS to CPU during transcription — no config needed. A dedicated GPU is not required; the entire pipeline runs on CPU (just slower).

[!NOTE] AMD GPUs: ROCm acceleration is Linux-only and opt-in — pick "AMD GPU (ROCm)" on the first-run setup screen or set OMNIVOICE_TORCH_VARIANT=rocm (docs/install/linux.md). In Docker/Podman, pull the dedicated ROCm image instead: ghcr.io/debpalash/omnivoice-studio:rocm (docs/install/docker.md). On Windows, AMD GPUs (incl. Ryzen AI iGPUs) run CPU-only: PyTorch has no Windows ROCm wheels, so Windows GPU acceleration is NVIDIA/CUDA-only (docs/install/windows.md).

[!IMPORTANT] macOS Intel (x86_64) is unsupported for the local backend: the app UI installs, but the Python backend cannot run because PyTorch no longer ships Intel-Mac wheels (#889). Intel-Mac users can still point the UI at a remote backend on another machine — see docs/install/macos.md.

🗣️ TTS Engines

14 engines, one picker. OmniVoice (default, 600+ languages) is always available; seven more are opt-in and auto-detected (CosyVoice 3, GPT-SoVITS, VoxCPM2, MOSS-TTS-Nano, KittenTTS, MLX-Audio, Sherpa-ONNX), plus six lazy-installed heavyweights (IndexTTS 2, OmniVoice GGUF, Supertonic 3, MOSS-TTS-v1.5, dots.tts, Confucius4-TTS). Switch in Settings → TTS Engine; the choice applies everywhere synthesis happens.

📊 The full matrix — 14 engines × platform × clone/instruct × license

Engine	Languages	Clone	Instruct	Linux	macOS ARM	Windows	License
OmniVoice (default)	600+	✅	✅	✅ CUDA/CPU	✅ MPS	✅ CUDA/CPU	Built-in
CosyVoice 3	9 + 18 dialects	✅	✅	✅ CUDA/CPU	✅ MPS	✅ CUDA/CPU	Apache-2.0
GPT-SoVITS	5	✅	—	✅ CUDA/CPU	—	✅ CUDA/CPU	MIT
VoxCPM2	30	✅	✅	✅ CUDA/CPU	✅ MPS	✅ CUDA/CPU	Apache-2.0
MOSS-TTS-Nano	20	✅	—	✅ CUDA/CPU	✅ CPU	✅ CUDA/CPU	Apache-2.0
KittenTTS	English	—	—	✅ CPU	✅ CPU	✅ CPU	MIT
MLX-Audio (Kokoro, Qwen3-TTS, CSM, Dia, …)	Multi	Varies	Varies	❌	✅ Native	❌	Varies
Sherpa-ONNX	20+	—	—	✅ CUDA/CPU	✅ CPU	✅ CUDA/CPU	Apache-2.0
IndexTTS 2 ⚡	Multi	✅	—	✅ CUDA	—	✅ CUDA	Apache-2.0
OmniVoice GGUF ⚡	600+	✅	✅	✅ CPU	✅ CPU	✅ CPU	Built-in
Supertonic 3 ⚡	31	—	—	✅ CPU	✅ CPU	✅ CPU	OpenRAIL-M
MOSS-TTS-v1.5 ⚡ (8B)	31	✅	—	✅ CUDA/CPU	✅ CPU	✅ CUDA/CPU	Apache-2.0
dots.tts ⚡ (2B)	24	✅	—	✅ CUDA/CPU	✅ CPU	❌	Apache-2.0
Confucius4-TTS ⚡	14	✅	—	✅ CUDA/CPU	✅ CPU	✅ CUDA/CPU	Apache-2.0

CUDA = GPU-accelerated · MPS = Apple Silicon Metal · CPU = runs everywhere, slower for large models · KittenTTS and MOSS-TTS-Nano run realtime on CPU · MLX-Audio is Apple Silicon only · ⚡ = lazy-registered (installed on first use)

Clone matters beyond single-clip generation: Video Dubbing (and any Batch job with a pinned voice) needs reference-audio cloning to preserve speaker identity, so picking a Clone-less engine (KittenTTS, Sherpa-ONNX, Supertonic 3) as the active engine fails those jobs up front with an actionable message instead of silently falling back to OmniVoice.

MOSS-TTS-v1.5 (8B, ~16 GB), dots.tts (2B, ~9 GB), and Confucius4-TTS are heavyweight opt-ins that run in their own isolated venv from a local clone. None claims Apple-Silicon MPS (CPU on Macs); dots.tts has no Windows path; Confucius4 wants CUDA (CPU works, ~17× realtime). Details: MOSS-TTS-v1.5 · dots.tts · Confucius4-TTS.

🎧 ASR Engines

10 engines — they power dictation, video dubbing, and subtitles. WhisperX is the cross-platform default (~100 languages, word-level timing); the rest are opt-in and auto-detected. Switch in Settings → Engines. Nine run fully on-device; the tenth (OpenAI-compatible) is an optional remote client for Qwen3-ASR or any compatible server.

📊 The full lineup — 10 engines, what each is best at, and compute-type notes

Engine	`OMNIVOICE_ASR_BACKEND`	Languages	Best for
WhisperX (default)	`whisperx`	~100	Dubbing & subtitles — word-level timing via wav2vec2 forced alignment
Faster-Whisper	`faster-whisper`	~100	Fast transcription on Linux / macOS / Windows (CTranslate2)
Faster-Whisper (isolated)	`faster-whisper-isolated`	~100	Same as Faster-Whisper but crash-isolated in a subprocess — an ASR crash won't take down the app
MLX Whisper	`mlx-whisper`	~100	Native Apple Silicon speed (Apple MLX / Metal)
PyTorch Whisper	`pytorch-whisper`	~100	CUDA / CPU fallback via 🤗 Transformers (no cuDNN 8 needed)
Parakeet TDT	`nemo-parakeet`	English + 25 EU	SOTA accuracy at ~10× realtime even on CPU, auto language detection (NVIDIA NeMo, CUDA/CPU)
Moonshine	`moonshine`	English	Edge / low-latency, ONNX
FunASR	`funasr`	50+	All-in-one multilingual — built-in VAD + inline speaker diarization (SenseVoice)
sherpa-onnx (live dictation)	`sherpa-onnx-asr`	25 EU + 90+	Live, faster-than-real-time dictation — small streaming/offline ONNX models (Parakeet TDT v3/v2, streaming Zipformer & Paraformer, Whisper Tiny), CPU, identical on macOS / Windows / Linux. Picked per-model in Settings → Voice.
OpenAI-compatible ⚠️ remote	`openai-compat-asr`	Server-dependent	A path to Qwen3-ASR today (self-hosted server, no transformers wait), any OpenAI-compatible transcription endpoint, or OpenAI's own API — no install, configure + test the connection in Settings → Engines (ASR tab). Audio leaves your machine to whatever server you point it at; see docs/engines/openai-compatible-asr.md.

Whisper-family engines cover ~100 languages; FunASR / SenseVoice adds an all-in-one multilingual path with built-in voice-activity detection and inline speaker diarization. sherpa-onnx powers the live dictation model picker — you talk and text appears as you speak. Every engine runs on-device — no API keys, no cloud.

GPU without efficient float16? On older NVIDIA GPUs (Maxwell/Pascal, GTX 16xx) or after a CTranslate2/cuDNN mismatch, the CTranslate2 ASR engines (WhisperX, Faster-Whisper) can't run float16 and OmniVoice automatically retries on int8 — no config needed. If transcription still fails, pin the compute type with the ASR_COMPUTE_TYPE env var (escape hatch): ASR_COMPUTE_TYPE=int8 (or float32 for CPU). Set it to int8 and restart the backend.

🏗️ Architecture

┌─────────────────────────────────────────────────────────────┐
│                    Frontend (React)                          │
│  DubTab · VoiceConsole · Stories · Audiobook · Gallery     │
│  Dictation · BatchQueue · Diagnostics · MCP Client          │
├─────────────────────────────────────────────────────────────┤
│                  Backend (FastAPI)                           │
│  100+ API endpoints · SSE+WSS streaming · SQLite            │
├──────────┬──────────┬──────────┬──────────┬────────────────┤
│ WhisperX │  Demucs  │OmniVoice │ Pyannote │ Engine Routing  │
│  (+7 ASR │  Source  │  (+10    │ Diariz-  │ ↳ GPU preflight │
│ engines) │  Sep.    │  TTS)    │ ation    │ ↳ No silent CPU │
└──────────┴──────────┴──────────┴──────────┴────────────────┘
         CUDA / MPS / ROCm / CPU (auto-detected + routed)

🔌 OpenAI-compatible API

Already have a script, agent, or tool that speaks OpenAI's audio API? Point it at http://localhost:3900/v1 — no key needed, no code changes. The backend ships a drop-in surface for the audio endpoints, wired to whichever TTS/ASR engine you have active (and yes, voice accepts your cloned voice-profile IDs).

Endpoint	What it does
`POST /v1/audio/speech`	TTS — text in; `mp3` / `wav` / `flac` / `opus` / `pcm` out. `tts-1` / `tts-1-hd` map to your active engine; OpenAI voice names (`alloy`, …) are accepted.
`POST /v1/audio/transcriptions`	STT — audio file in; `json`, `text`, `verbose_json`, `srt`, or `vtt` out. `whisper-1` maps to your active ASR engine.
`GET /v1/audio/voices`	OmniVoice extension — lists every voice profile and engine, so clients can discover your clones.

curl http://localhost:3900/v1/audio/speech \
  -H "Content-Type: application/json" \
  -d '{"model": "tts-1", "voice": "alloy", "input": "Generated on my own hardware.", "response_format": "wav"}' \
  --output speech.wav

from openai import OpenAI
client = OpenAI(base_url="http://localhost:3900/v1", api_key="none")  # any string works — nothing checks it

result = client.audio.transcriptions.create(model="whisper-1", file=open("clip.wav", "rb"))
print(result.text)

Want the whole surface (100+ endpoints)? The full REST API reference is embedded in the app — Settings → OpenAPI Reference (Scalar-powered), or the {} button in the footer.

📓 Run on Google Colab

No local GPU? The official notebook (notebooks/OmniVoice_Studio_Colab.ipynb) boots the full app — web UI included — on a free Colab T4: it builds the frontend in-notebook, installs the backend with uv (reusing Colab's preinstalled CUDA PyTorch), and opens the UI through Colab's built-in port proxy. No third-party tunnels, no API keys. It then walks the whole feature surface as a guided API tour with inline playback: multilingual TTS, voice cloning and design, saved voice profiles, transcription, AI-watermark detection, the OpenAI-compatible API, a multi-voice story, a chaptered m4b audiobook, and a miniature video dub with vocal-isolation stems.

🤝 Agent Skills

Teach your AI agent (Claude Code, Cursor, Codex, …) to use OmniVoice with one command:

npx skills add debpalash/omnivoice-studio

Ships two skills: omnivoice — speak and transcribe through your local install (including your cloned voices) from any agent, free and offline; and oss-maintainer — the maintainer methodology this project is run with, for anyone running their own OSS project with an agent.

🗺️ Roadmap

🔜 Up Next

🎬 Lip-sync v2 — visual speech timing with wav2lip
🌐 Hosted Demo — try OmniVoice without installing anything
🔌 Plugin Marketplace — community-contributed TTS engines and effects
🎵 Real-time Voice Changer — live microphone transformation during calls

✅ Everything shipped so far — the receipts, by category

Category	Features
Longform	Audiobook editor (text/EPUB/PDF → chaptered .m4b), Stories multi-voice editor, two-pass loudnorm mastering, crash-resume for interrupted renders, pronunciation control + SSML-lite prosody
Dubbing	Full pipeline (transcribe→translate→synthesize→mux), scene-aware splitting, lip-sync scoring, streaming TTS, per-speaker voice assignment, Smart Fit timing + second-pass QC, dedicated Dub home
Voice	Zero-shot cloning, voice design, A/B comparison, voice preview widget, gallery with favorites/tags, portable persona bundles (`.ovsvoice`), voice console workspace
Audio	Demucs vocal isolation, per-segment gain, selective track export, stem/SRT/VTT/MP3 export, unlimited-length TTS via sentence-chunked generation
Multi-Lang	Multi-language batch picker, batch dubbing queue with sequential GPU execution
Diarization	Pyannote ML diarization, auto speaker clone extraction, per-speaker voice assignment
ASR	9 engines (WhisperX, Faster-Whisper, isolated Faster-Whisper, MLX Whisper, PyTorch Whisper, Parakeet TDT, Moonshine, FunASR/SenseVoice, sherpa-onnx live dictation), crash-isolated subprocess backend
TTS	14 engines (OmniVoice, CosyVoice 3, GPT-SoVITS, VoxCPM2, MOSS-TTS-Nano, KittenTTS, MLX-Audio, Sherpa-ONNX, + lazy: IndexTTS 2, OmniVoice GGUF, Supertonic 3, MOSS-TTS-v1.5, dots.tts, Confucius4-TTS), engine routing with GPU preflight
Infra	Docker deployment, CUDA/MPS/ROCm auto-detect, cuDNN 8 compat, VRAM-aware model offloading, engine routing (no silent CPU fallback), diagnostics suite & error journal, restricted-network mirror support
AI Provenance	AudioSeal invisible watermarking (SynthID-like), video logo overlay, watermark detection API
UX	Undo/redo, keyboard shortcuts, drag-and-drop, session persistence, glassmorphism design system, UI scale fix for Linux/WebKitGTK
Real-time Events	WebSocket event bus — instant sidebar refresh on data mutations, exponential backoff reconnect
State Management	Zustand store migration — `uiSlice`, `pillSlice`, `dubSlice`, `generateSlice`, `prefsSlice`, `glossarySlice`
Desktop	Cross-platform Tauri installers (macOS DMG — Apple Silicon; Intel unsupported for the local backend, #889 — Windows MSI, Linux deb/AppImage), auto-update infrastructure, single-instance enforcement, close-to-tray, macOS Gatekeeper fix
Dictation	Global system-wide hotkey (`⌘+⇧+Space`), frameless floating widget, streaming ASR via WebSocket, auto-paste, customizable hotkey, local-LLM transcript refinement
Batch Pipeline	Full batch TTS: extract → transcribe → translate → generate → mix → export, with live progress tracking
MCP Server	OmniVoice as a local TTS/STT provider for Claude, Cursor, and any MCP client
Remote Backend	Point the desktop UI at a remote backend URL with bearer auth (Tailscale-documented)
Reliability	Stall watchdog on bootstrap splash, per-engine GPU compatibility matrix, actionable errors for non-executable engine binaries, setuptools auto-repair

OmniVoice Studio is built by one developer using Claude Code and AI agents — and the agent bills are real (thousands of dollars over the last three months). If OmniVoice has created value for you, covering a slice of those bills keeps development full-time.

This month's agent bill fund

_{Every dollar goes directly to agent bills — keeping OmniVoice development continuous.}

_{More apps from the creator of OmniVoice Studio — same local-first philosophy:
Opal 💠 (play everything — the media player for the AI era) ·
memxt 🧠 (local memory for Claude Code & coding agents).
A ⭐ on those helps too → details below.}

🌟 Sponsors

OmniVoice is free and AGPL-3.0 — no paid tier, no SaaS revenue. Sponsors keep development going, and in return get a logo slot here, in the app, and (for top tiers) on the project website. It's a thank-you, never a paywall. See tiers & become a sponsor →

Your logo here — become a sponsor

_{💡 GitHub also shows a Sponsor button at the top of this repo, wired to the same links via .github/FUNDING.yml.}

💬 Community

_{We respond to setup questions within hours, not days.}

What happens in there

Channel	What happens there
`#announcements`	Release news and the big moments — new versions land here first
`#releases` + `#changelog`	Every build and exactly what's inside it
`#issues`	Bug reports as forum posts — triaged straight into GitHub issues
`#ideas`	Feature requests, discussed and voted on
`#discuss-ideas`	Design talk before things get built
`#general`	Setup help, GPU troubleshooting, and showing off your dubs

🤝 Contributing

Yes please — bug fixes, new TTS engine adapters, UI improvements, docs, translations. All of it.

📖 Read the Contributing Guide for setup, code style, and PR workflow
🐛 Browse good first issues
💬 Join our Discord to discuss ideas or ask for help

❓ FAQ

Is this really as good as ElevenLabs?

Honest answer: it depends on what you're doing.

Where OmniVoice is genuinely competitive: voice cloning from a clean reference clip (state-of-the-art open diffusion TTS), language coverage (646 languages vs. their 32), and everything structural — no per-character billing, no usage caps, no audio leaving your machine, full pipeline customizability (14 TTS engines, 10 ASR engines, your choice of translation).

Where ElevenLabs still wins: out-of-the-box consistency and polish, especially for English TTS. Their one model is heavily tuned; our quality depends on which engine you pick, your hardware, and — for cloning — the reference audio (a dry, close-mic clip clones dramatically better than a noisy or echoey one).

For dubbing specifically: a dub is a chain — transcription → translation → cloning → synthesis — only as good as its weakest link on your source material. If parts come out incoherent, check the segment table's original text first: when the transcription is already wrong, switch the ASR engine or use cleaner source audio — that's usually the fix, not the voice.

Try it on your real material — it's free and takes one download. Many users replace ElevenLabs outright; some keep both. Both outcomes are fine with us.

Does it work on Apple Silicon (M1/M2/M3/M4)?

Yes. MPS acceleration is auto-detected. MLX-optimized Whisper models are available for faster transcription on Apple hardware. Intel Macs are not supported: the app UI installs, but the local Python backend cannot run because PyTorch no longer ships Intel-Mac wheels (#889) — an Intel Mac can only be used with a remote backend.

How much VRAM do I need?

4 GB minimum. With ≤8 GB, the TTS model is automatically offloaded to CPU during transcription. With 8+ GB, everything runs on GPU simultaneously. No GPU at all? CPU mode works — just slower (~3× for TTS).

Can I use this commercially?

Yes — commercial use is free under the AGPL-3.0: run it, sell the audio you make, dub client videos, deploy it across your team. One obligation: if you modify OmniVoice and offer the modified version to others over a network, you must share that modified source under the same terms. Embedding it in a closed-source product instead? A commercial license is available — see License.

What languages are supported?

646 languages for TTS via the OmniVoice model. Transcription (WhisperX) supports 99 languages. Translation coverage depends on the target language pair.

Can I add my own TTS engine?

Yes. Subclass TTSBackend in backend/services/tts_backend.py and add it to the _REGISTRY dictionary — ~50 lines. The fourteen built-in engines all work this way; see TTS Engines.

Does OmniVoice collect any data about me?

Not unless you explicitly say yes. On first run the app asks — one screen, two equal-weight buttons, no pre-ticked box — and until you answer yes, OmniVoice sends nothing: no analytics, no telemetry, no accounts, no phone-home. Skipping the question means no. Your text, audio, voices, and projects never leave your machine either way.

If you do opt in (also togglable anytime under Settings → Privacy → "Help improve OmniVoice"), what's sent is anonymous, content-free usage stats: generations (engine, language, generation time, character count, error type), plus app lifecycle — an install ping, updates (version-to-version), crashes (error class and a bucketed uptime, never logs), error types (capped, deduplicated), and a single uninstall ping if you remove it. Never your text, audio, file names, or anything identifying — enforced in code by a property allowlist (backend/core/analytics.py), not just a promise. Source builds have no analytics destination at all, so they never even ask. Your own numbers live in Settings → Usage, computed locally, sent nowhere.

How do I uninstall it / remove all its data?

OmniVoice is fully local — uninstalling is just deleting the app plus the folders it wrote (model cache, Python env, your voices/projects, config). Run scripts/uninstall.sh (macOS/Linux) or scripts\uninstall.ps1 (Windows) — it prints every folder with its size as a dry-run first, then deletes on --yes. The full per-platform path list and app-removal steps are in docs/install/uninstall.md.

📜 License

OmniVoice Studio is free and open-source software under the GNU Affero General Public License v3.0 (AGPL-3.0).

Free for any use — including commercial and internal business use. Run it, sell the audio you produce with it, dub your own or clients' videos, roll it out across your team — all free, no license needed. As a network copyleft license, AGPL adds one obligation: if you modify OmniVoice Studio and offer that modified version to others over a network, you must make the complete corresponding source of your modified version available to them under the same AGPL-3.0 terms.

A commercial license is available for organizations that want to embed OmniVoice Studio in a closed-source or proprietary product or service without the AGPL-3.0 copyleft obligations. Pricing tiers coming soon. Inquiries: OmniVoice@palash.dev.

The bundled omnivoice/ TTS model by Han Zhu remains Apache-2.0 upstream. See LICENSE for the full, binding terms, and LICENSE-NOTICE.md for the plain-language summary and scope.

🙏 Acknowledgments

OmniVoice Studio is built on the shoulders of exceptional open-source work:

Project	Role
OmniVoice (k2-fsa)	Zero-shot diffusion TTS engine — the core voice synthesis model
WhisperX	Word-level speech recognition and alignment
Demucs (Meta)	Music source separation for vocal isolation
Pyannote	Speaker diarization — who said what
CTranslate2	Optimized Transformer inference on CPU and GPU
AudioSeal (Meta)	Invisible neural audio watermarking for AI provenance
Tauri	Native desktop app framework
Supertone / Supertonic 3	ONNX TTS engine — 31 languages, CPU-efficient
Sherpa-ONNX	WASM-ready universal TTS/ASR runtime
GPT-SoVITS	Zero-shot TTS engine — 5 languages, RTF 0.014

🧰 More local open-source from the maker

Like the local-first philosophy? It runs in the family — same maker, same rule: your data stays on your machine.

Opal 💠

Play everything. The media player for the AI era.

_{Video, anime, comics, torrents, Jellyfin & Plex — one player for all of it, with local AI memory and context built in. Written in Zig, runs on macOS & Windows.}

memxt 🧠

The fastest benchmarked open-source AI memory system.

_{Local long-term memory for Claude Code and coding agents — an MCP server on SQLite + embeddings, 100% on your machine. Your agent finally remembers yesterday.}

If you read this far, you're our kind of person.
⭐ Star this repo so others can find it too.
💬 Join the Discord to share what you build.
❤️ Support development — fund the AI agent bills that keep OmniVoice shipping.

Open Sources

OmniVoice-Studio

About this project

OmniVoice Studio

The open-source ElevenLabs alternative.

📸 See it in action

✨ Features

🎙️ Voice Cloning

🎨 Voice Design

🎬 Video Dubbing

📖 Audiobook Editor

🎭 Stories

⌨️ Dictation Widget

🔐 100% Local

🤖 MCP Server

⚡ Quickstart

💡 Why OmniVoice?

🖥️ System Requirements

🗣️ TTS Engines

🎧 ASR Engines

🏗️ Architecture

🔌 OpenAI-compatible API

📓 Run on Google Colab

🤝 Agent Skills

🗺️ Roadmap

🔜 Up Next

🌟 Sponsors

💬 Community

🤝 Contributing

❓ FAQ

📜 License

🙏 Acknowledgments

🧰 More local open-source from the maker

Opal 💠

memxt 🧠

Related Projects

awesome-design-md

llm-course

CL4R1T4S

Open Sources

Everything worth knowing in AI.

OmniVoice-Studio

About this project

OmniVoice Studio

The open-source ElevenLabs alternative.

📸 See it in action

✨ Features

🎙️ Voice Cloning

🎨 Voice Design

🎬 Video Dubbing

📖 Audiobook Editor

🎭 Stories

⌨️ Dictation Widget

🔐 100% Local

🤖 MCP Server

⚡ Quickstart

💡 Why OmniVoice?

🖥️ System Requirements

🗣️ TTS Engines

🎧 ASR Engines

🏗️ Architecture

🔌 OpenAI-compatible API

📓 Run on Google Colab

🤝 Agent Skills

🗺️ Roadmap

🔜 Up Next

💜 Sponsor / Donate

🌟 Sponsors

💬 Community

🤝 Contributing

❓ FAQ

📜 License

🙏 Acknowledgments

🧰 More local open-source from the maker

Opal 💠

memxt 🧠

Related Projects

awesome-design-md

llm-course

CL4R1T4S