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A Soniqo project.
Open-source desktop app for content creators. Clone a voice from a short reference clip, write a script line by line, and synthesize the whole thing in that voice — with inline emotion markers for tone.
A blind A/B/C — a real voice, the same voice cloned locally by Speech Studio on a MacBook, and the same voice cloned by ElevenLabs in the cloud. Can you tell which is which?
Watch on YouTube → (30 sec)
Status: v0 — audio-only MVP. Runs on macOS 15+ (Apple Silicon) and Windows / Linux (x86_64): macOS clones via MLX, Windows/Linux via
speech-core's on-device LiteRT backend. Video playback against the timeline and an audio-over-video export step are on the roadmap.
- Drop a short reference clip of a speaker → register a cloned voice. Repeat for as many speakers as you need.
- Write a script line per clip and pick which speaker says it. Wrap the line in an emotion marker —
(whispering) Just stay quiet for a moment, please.— and the synth will follow that direction. - Hit Synthesize to render every line in the assigned cloned voice. The synth pipeline auto-grades each take with on-device ASR and retries with a different seed if the line came out wrong.
- Play the script to hear the whole scene back-to-back. Export a single WAV mix (export wiring is in progress).
The clone is local. The synth is local. No audio leaves your machine.
- Tauri 2 shell (Rust + the OS-native WebView) so the shipped app is a small native binary, not a Chromium fork.
- React + Vite frontend for the timeline, voice library, and script editor.
- A warm sidecar process holds the speech engine resident so per-line synthesis is fast after the first warm-up. Tauri spawns it once and talks NDJSON over stdin/stdout. On macOS this is the Swift sidecar (
swift-sidecar/, MLX); on Windows/Linux the C++ sidecar (core-sidecar/, LiteRT). - VoxCPM2 is the speech engine on every platform — via
speech-swift(MLX) on macOS andspeech-core(LiteRT) on Windows/Linux. On macOS, CosyVoice3 and Qwen3-TTS are kept as fallbacks behindSONIQO_TTS_ENGINE=cosyvoice/qwen3.
Wrap a line in a parenthetical tag to steer the prosody:
(dramatic) I never thought we'd make it this far.
(warm) I knew you would make it, no matter what.
(whispering) Just stay quiet for a moment, please.
(intense) Then we end this together. Tonight.
Supported tags include soft, warm, whispering, intense, excited, happy, calm, serious, surprised, sad, angry, dramatic, laughs. Each maps to a short natural-language style instruction that's passed to the model; custom tags (e.g. (slow and dreamy)) pass through verbatim.
Grab the latest build from the releases page:
| Platform | Artifact | Status |
|---|---|---|
| macOS (Apple Silicon) | .dmg |
✅ Published |
| Windows (x86_64) | .msi / .exe |
✅ Published |
| Linux (x86_64) | .deb / .AppImage |
✅ Published |
Every platform downloads its speech model on first run (resumable) and caches it, so the installers stay small:
- macOS —
.dmg(~46 MB); drag into/Applications. First run pulls ~2.75 GB of MLX weights into~/.cache/huggingface/hub/. - Windows —
.msior the NSIS-setup.exe. First run pulls the ~4.6 GB VoxCPM2-LiteRT bundle into%LOCALAPPDATA%\speech-core. - Linux —
.debor.AppImage. First run pulls the same bundle into~/.cache/speech-core.
The builds are unsigned: Windows SmartScreen needs More info → Run anyway, and macOS needs a right-click → Open the first time to bypass Gatekeeper.
Common: Rust 1.95+ via rustup (. "$HOME/.cargo/env" if cargo isn't on PATH), Node 20+ and pnpm 11+.
- macOS: 15+ on Apple Silicon (M1/M2/M3/M4), Xcode 26+ (Swift 6.0 toolchain).
- Windows / Linux (x86_64): a C++17 toolchain + CMake 3.16+, and a built
speech-corecheckout with the LiteRT backend (-DSPEECH_CORE_WITH_LITERT=ON -DLITERT_DIR=...) plus theVoxCPM2-LiteRTmodel bundle.
pnpm install # installs the frontend + Tauri CLI
cd swift-sidecar && swift build # builds the Swift sidecar
cd .. && pnpm tauri dev # launches the app, hot-reloads the UISame ~2.75 GB model download on first synth.
pnpm install
# Build the C++ sidecar against your speech-core checkout (defaults to ../speech-core):
cmake -B core-sidecar/build core-sidecar -DSPEECH_CORE_DIR=../speech-core
cmake --build core-sidecar/build --config Release
# Point it at the VoxCPM2-LiteRT bundle, then launch:
export SONIQO_VOXCPM2_BUNDLE_DIR=/path/to/speech-core/scripts/models-voxcpm2
pnpm tauri devMeasured through the 4-line demo on an Apple Silicon Mac (M-series, unified memory). Numbers are MLX's own accounting; OS RSS adds ~500 MB of process overhead on top.
| Variant | Disk | Active | Peak | Default |
|---|---|---|---|---|
aufklarer/VoxCPM2-MLX-int8 |
2.75 GB | 3.1 GB | 5.4 GB | ✅ |
aufklarer/VoxCPM2-MLX-bf16 |
4.6 GB | 9.1 GB | 11.4 GB | |
aufklarer/VoxCPM2-MLX-int4 |
1.75 GB | (not benchmarked) |
The MLX buffer cache is capped at 1 GB (SONIQO_MLX_CACHE_MB to override) — without that cap, peak grows to tens of GB on long sessions as varying-shape buffers accumulate. Override the default model with SONIQO_VOXCPM2_MODEL_ID=aufklarer/VoxCPM2-MLX-bf16 if you want the higher-fidelity weights.
Hit Load demo in the top bar. It bootstraps a Scene 04 storyboard with two cloned voices (Anna and Marek) and four lines of dialogue — one with each emotion marker — then synthesizes everything via VoxCPM2.
cd swift-sidecar && swift build -c release
cd .. && pnpm tauri build # produces .app + .dmg under src-tauri/target/release/bundle/speech-swift— Apple Silicon speech engines (VoxCPM2, CosyVoice3, Qwen3-TTS, Parakeet, Silero VAD).speech-core— C++ engines (VoxCPM2 cloning on Windows/Linux, plus STT, VAD, denoise).
See AGENTS.md for project conventions. Short version: branch → PR → merge, no force-pushes, no AI co-author trailers, never commit unless explicitly asked.
Apache License 2.0 — same as speech-swift and speech-core.