8f4aeca2f1 feat(asr): add Parakeet TDT 0.6B engine via sherpa-onnx (#802)
* feat(asr): add Parakeet engine via sherpa-onnx

Adds a "parakeet" engine backed by sherpa-onnx, running NVIDIA Parakeet
TDT 0.6B int8 models on CPU: v3 (25 European languages, auto-detected)
and v2 (English). Output is punctuated and capitalized.

On an Intel Core Ultra 7 155H it decodes at about 12x realtime on CPU
(RTF 0.08), roughly 8x faster than whisper.cpp large-v3-turbo over the
same clips with its Vulkan GPU backend (RTF 0.59). Being a transducer it
also has no 30s window to pad, so a short push-to-talk utterance returns
in ~0.3s instead of ~2.4s.

Follows the existing engine layout: utils/parakeet_model_info.py holds
the catalog and the get_model_path / is_model_downloaded /
list_downloaded_models / delete_model helpers, while _init_parakeet /
_transcribe_with_parakeet / _download_parakeet_model follow the same shape as their
whisper.cpp counterparts and reuse _stream_model_download for progress
and cancellation.

Registered in the engine dispatch, the settings engine/model/language
pickers, the model info card, the download prompts, the unused-downloads
list and install.sh.

Models download to <models_dir>/parakeet/<model>/ via temp files renamed
on success; is_model_downloaded requires all four files, so an
interrupted download is retried rather than loaded.

Requires the new "parakeet" extra (sherpa-onnx).

* fix(install): write only the engine key for parakeet

The parakeet branch duplicated a full default config.json. ConfigManager
deep-merges DEFAULT_CONFIG on load, so every other key was redundant:
a config holding only "engine": "parakeet" still resolves
parakeet_model_size to v3-european along with the VAD, shortcut and
text-injection defaults.

* fix(install): keep push-to-talk defaults and switch existing configs

Writing only the engine key left config.json without a shortcuts
section, which _migrate_shortcuts_config reads as a pre-push-to-talk
upgrade and pins back to ctrl+ctrl/toggle - contradicting the
installer's own "Hold Right Alt while you speak" message. Seed that
section too.

Point the config at parakeet with set_configured_engine rather than only
on first create, so --engine=parakeet also switches a machine that
already has a config.json, and give print_welcome_message a parakeet arm
so the summary is not blank.

The interactive picker overwrites SELECTED_ENGINE, so document the flag
combination that reaches this branch.

* fix(asr): pin Parakeet bundles and report one progress bar

Pin each bundle to a Hugging Face commit instead of resolve/main, so a
file replaced upstream cannot change what an install downloads. This is
the same approach whispercpp_model_info takes with its pinned revision.

Remap each file's progress into its slice of the bundle. The four files
were reported through the single-file downloader independently, so the
fraction ran to 1.0 and restarted four times; it now advances once and
names the file being fetched.

* fix(asr): reject a truncated Parakeet download

_stream_model_download only rejects an empty body, so a truncated but
nonempty response was renamed into the model directory and then reported
as installed, because is_model_downloaded checks existence.

Record the byte size of each file at the pinned revision and check it
before the rename, the same order whisper.cpp verifies its digest in. A
short file is a truncated transfer rather than an upstream change, since
the revision is pinned, so it raises and the temp file is removed.

* style(asr): annotate the Parakeet model catalog

mypy inferred the catalog values as object, so reading file_sizes out of
an entry raised attr-defined and no-any-return under `just typecheck`.

* fix(asr): pin Parakeet digests in model_checksums.txt

AGENTS.md requires every speech model to be verified against a pinned
digest before install, failing closed on an unpinned one. Parakeet was
checking only the byte size.

Teach scripts/generate-model-checksums.py to emit Parakeet entries: the
ONNX files are LFS so Hugging Face publishes their sha256, and tokens.txt
is hashed from the downloaded bytes the way VOSK archives are. Several
bundles ship the same file names, so a key carries the model name.

_download_parakeet_model now calls verify_model_file before the rename
and catches ChecksumError alongside the other download failures, matching
the whisper.cpp downloader.

* fix(asr): verify on-disk Parakeet models before load

Existing bundle files were trusted by path alone, so a leftover or
copied-in tree could reach sherpa-onnx unchecked. Hash each file against
its pin on download skip and on init, and cover the Parakeet pins in CI.

* fix(ui): hide Parakeet language picker that ignores the setting

Parakeet language coverage is the model choice, not a catalog language.
Hide the picker and persist auto so Settings does not write a lying value.

* fix(asr): normalize Parakeet language to auto at startup

CLI --language and stale saved languages still reached SpeechRecognitionManager
even though Parakeet ignores catalog language. Force auto on the shared helper
used by main and the manager so stored settings stay honest.

* fix(ui): restore language after leaving Parakeet

Remember the prior Whisper/cpp language across a Parakeet visit so switching
back does not leave recognition stuck on auto. Keep Parakeet forced to auto
and the picker hidden. Also satisfy black on the startup normalizer path.

* fix(ui): keep language memory across Vosk fallback

Vosk's unsupported-language en-us coercion was writing into
_last_non_parakeet_language, so Whisper→Parakeet→Vosk→Whisper restored
en-us instead of the user's Greek (or other) preference. Remember the
pre-coercion catalog language and prefer it when leaving Vosk.

* fix(ui): keep language memory when entering Parakeet from Vosk

Vosk's coerced en-us fallback was still written into
_last_non_parakeet_language on Parakeet entry, so Vosk→Parakeet→Whisper
restored en-us instead of the pre-coercion preference (Greek or auto).
Share one coerced-fallback predicate across entry, leave-Vosk, and language
sync, and cover those paths with regression tests.

* fix(tests): set initializing flags false on language-change stubs

Plain Mock attributes are truthy and were short-circuiting the handler.

---------

Co-authored-by: Alex Thunder <AlexThunder@gmail.com>
2026-09-07 14:32:13 -07:00
2025-05-25 23:20:08 -05:00
2026-08-23 01:33:08 -07:00

Vocalinux

Vocalinux

Voice-to-text for Linux, finally done right!

Ubuntu Debian Fedora Arch openSUSE

Privacy: on-device X11 & Wayland PRs Welcome License: AGPL-3.0 Python 3.11+

Discord VocaHQ Follow on X

GitHub release PyPI AUR

Linux has always punched above its weight, except when it comes to voice typing. Vocalinux fixes that.

It's a free, AGPL-3.0-licensed desktop app that lets you dictate text into any application, on X11 or Wayland, using on-device speech recognition after you download a model. Pick from three engines (whisper.cpp, OpenAI Whisper, or VOSK), get automatic GPU acceleration via Vulkan, and control it all with customizable keyboard shortcuts: toggle or push-to-talk.

Models are downloaded once. After that, speech-to-text stays on your machine. No Voca account is required. Just speak and type.

📚 What's New in v0.16.2

0.16.2 is a stability patch on the 0.16 series. Dictation types again on KDE when a leftover IBus daemon is not the session IM, Wayland and IBus keyboard shortcuts actually fire through wtype/ydotool, "delete that" sends real BackSpace, and the installer pulls glslc on Fedora/Arch. Release builds pin builders and ship checksums; AUR PKGBUILD and distro docs get CI gates.

0.16 series highlights

Feature Description
Update checker Settings → About checks stable/nightly channels; tray shows Update Available when GitHub has a newer release (#631, #645)
Right Alt PTT default New installs default to hold Right Alt (push-to-talk); existing configs keep their shortcut (#648)
Searchable languages Type to filter the Speech Model language list (#672)
Delete unused models Remove leftover downloaded speech models from Settings (#671)
AGPL-3.0 License aligned with other VocaHQ projects (#660)
Family mic icons App icon, tray states, and site favicons use the shared Voca family mic (#704)
Tone picker Settings → Audio: Lift, Flick, Ember, Step, Voca, Soft, Chirp, Scale, Drop, Glass, Off, plus Preview. New installs default to Voca. Catalog uses family preview WAVs (#707, #708)
Installer Justfile, uv lockfiles, distro python3-gi required (no pip sdist of PyGObject). Epic #701 still open (#700, #705, #706)

Bug fixes in v0.16.2

  • KDE inject: skip leftover IBus when it is not the session IM so dictation types into Kate, browsers, and terminals (#753, fixes #752)
  • Wayland / IBus shortcuts: wtype and ydotool deliver real chords; IBus sessions route shortcuts to a virtual-keyboard tool (#715, #716)
  • Delete that: send real BackSpace key events instead of U+0008 text (#714)
  • Installer: Fedora and Arch need glslc/shaderc, not glslang (#763, #604)
  • Nightly / release: stamp version before build; release integrity checksums and pinned builders (#762, #759)
  • CI / docs: AUR PKGBUILD gate on every PR; distro CI matches the docs (#772, #773)
  • Site: VocaGateway family card is Beta; README logo, badges, privacy copy (#765, #764)

See docs/UPDATE.md and the full changelog.


Features

  • 🎤 Toggle or Push-to-Talk activation modes
  • ⚡ Real-time transcription with minimal latency
  • 🌎 Universal compatibility across all Linux applications
  • 🔒 On-device after model download — speech-to-text stays on your machine
  • 🤖 whisper.cpp by default - High-performance C++ speech recognition
  • 🎮 Universal GPU support - Vulkan acceleration for AMD, Intel, and NVIDIA
  • 🎨 System tray integration with visual status indicators
  • 🚀 Start on login support via XDG autostart (desktop-session startup)
  • 🔊 Pleasant audio feedback - smooth gliding tones, headphone-friendly
  • ⚙️ Graphical settings dialog for easy configuration
  • 📦 3 engine choices - whisper.cpp (default), OpenAI Whisper, or VOSK

📸 Screenshots

Vocalinux in action. Settings gallery shots may lag the newest UI. Full gallery on the website screenshots page.

Product

Transcription in Action
Real-time voice-to-text transcription
System Tray
System tray with listening indicator
About View
About & Updates in Settings
Log Viewer
Log viewer for debugging

Settings

Speech Engine settings
Speech Engine
Recognition settings
Recognition
Audio settings
Audio
Performance settings
Performance
General settings
General
Advanced tuning and settings
Advanced

🚀 Quick Install

Our new interactive installer guides you through setup with intelligent hardware detection:

curl -fsSL raw.githubusercontent.com/VocaHQ/vocalinux/main/install.sh -o /tmp/vl.sh && bash /tmp/vl.sh

Choose your engine:

  1. whisper.cpp ⭐ (Recommended) - Fast, works with any GPU via Vulkan
  2. Whisper (OpenAI) - PyTorch-based, NVIDIA GPU only
  3. VOSK - Lightweight, works on older systems

The installer will:

  • Auto-detect your hardware (GPU, RAM, Vulkan support)
  • Recommend the best engine for your system
  • Download the appropriate model (~74MB for the default whisper.cpp tiny model)
  • Install neural VAD support when ONNX Runtime is available
  • Install in ~1-2 minutes (vs 5-10 min with old Whisper)

Note

: Always installs the latest release. For a specific version, check GitHub Releases.

Installation Options

Default (whisper.cpp - recommended):

curl -fsSL raw.githubusercontent.com/VocaHQ/vocalinux/main/install.sh -o /tmp/vl.sh && bash /tmp/vl.sh

Fastest installation (~1-2 min), universal GPU support via Vulkan.

Whisper (OpenAI) - if you prefer PyTorch:

curl -fsSL raw.githubusercontent.com/VocaHQ/vocalinux/main/install.sh -o /tmp/vl.sh && bash /tmp/vl.sh --engine=whisper

NVIDIA GPU only (~5-10 min, downloads PyTorch + CUDA).

VOSK only - for low-RAM systems:

curl -fsSL raw.githubusercontent.com/VocaHQ/vocalinux/main/install.sh -o /tmp/vl.sh && bash /tmp/vl.sh --engine=vosk

Lightweight option (~40MB), works on systems with 4GB RAM.

Arch Linux (AUR)

yay -S vocalinux

See docs/AUR.md.

Flatpak (any distro)

GitHub Releases attach Vocalinux-<version>-x86_64.flatpak and Vocalinux-<version>-aarch64.flatpak. After the Flathub GNOME runtime is present, install with flatpak install --user ./Vocalinux-<version>-x86_64.flatpak. Bundles do not auto-update.

For a local build (contributors), use the bundled manifest:

flatpak install flathub org.gnome.Platform//50 org.gnome.Sdk//50
flatpak-builder --user --install --force-clean build-dir \
  packaging/flatpak/com.vocalinux.Vocalinux.yml
flatpak run com.vocalinux.Vocalinux

The Flatpak ships the whisper.cpp engine with Vulkan GPU support and runs through XWayland on Wayland sessions. See packaging/flatpak/README.md for build details and permissions. It is not on Flathub: the submission (flathub/flathub#9368) was closed on 2026-07-23 on policy grounds. Release .flatpak assets are tracked in #784; the longer-term channel is #167.

Alternative: Install from Source

# Clone the repository
git clone https://github.com/VocaHQ/vocalinux.git
cd vocalinux

# Run the interactive installer (engine picker + GPU detection)
./install.sh

# Or pick the engine up front
./install.sh --engine=whisper_cpp   # whisper.cpp (default, GPU-accelerated)
./install.sh --engine=vosk          # lightweight VOSK
./install.sh --engine=parakeet --auto   # Parakeet (25 European languages, CPU)

The installer handles everything: system dependencies, Python environment, speech models, and desktop integration.

Snap (Ubuntu Snap Store)

In-repo recipe: snap/snapcraft.yaml (issue #48). Store listing: snapcraft.io/vocalinux. Pack and upload steps: docs/INSTALL.md.

sudo snap install vocalinux --edge   # current public channel (0.16.2 refresh)
# sudo snap install vocalinux --candidate   # after candidate release
# sudo snap install vocalinux               # after stable promotion
sudo snap connect vocalinux:audio-record   # if mic is not auto-connected
sudo snap connect vocalinux:raw-input      # global keyboard shortcuts (evdev)

🌙 Nightly Releases (Bleeding Edge)

For developers and early adopters who want to test the latest features, check out our GitHub Releases page which includes both beta and nightly builds.

⚠️ Warning: Nightly releases contain the absolute latest code and may be unstable. For production use, we recommend using the latest beta release.

Nightly builds are automatically generated from the main branch every day. They include all merged changes but haven't undergone the same testing as beta releases.

Release Channels:

  • Beta (Recommended) - Tested pre-releases with known features
  • Nightly - Untested bleeding edge with latest commits

After Installation

# If ~/.local/bin is in your PATH (recommended):
vocalinux

# Or activate the virtual environment first:
source ~/.local/bin/activate-vocalinux.sh
vocalinux

# Or run directly:
~/.local/share/vocalinux/venv/bin/vocalinux

Or launch it from your application menu!

📋 Requirements

  • OS: Linux (tested on Ubuntu 24.04+, Debian 12+, Fedora 42+, Arch Linux, openSUSE Tumbleweed)
  • Python: 3.11 or newer
  • Display: X11 or Wayland
  • Hardware: Microphone for voice input

Note: See Distribution Compatibility for distribution-specific information and experimental support for Gentoo, Alpine, Void, Solus, and more.

🎙️ Usage

Voice Dictation

  1. Push-to-talk (default): Hold Right Alt (Option on Mac-layout keyboards) and speak
  2. Speak clearly into your microphone
  3. Release the key to stop, or switch to Toggle mode in Settings (double-tap a key to start/stop)

Voice Commands

Command Action
"new line" Inserts a line break
"period" / "full stop" Types a period (.)
"comma" Types a comma (,)
"question mark" Types a question mark (?)
"exclamation mark" Types an exclamation mark (!)
"delete that" Deletes the last sentence
"capitalize" Capitalizes the next word

Command Line Options

vocalinux --help                  # Show all options
vocalinux --debug                 # Enable debug logging
vocalinux --engine whisper_cpp    # Use whisper.cpp engine (default)
vocalinux --engine whisper        # Use OpenAI Whisper engine
vocalinux --engine vosk           # Use VOSK engine
vocalinux --model medium          # Use medium-sized model
vocalinux --model medium.en-q5_0  # Use exact whisper.cpp model variant
vocalinux --model large-v3-turbo  # Use large-v3 Turbo with whisper.cpp
vocalinux --wayland               # Force Wayland mode
vocalinux --start-minimized       # Start without first-run modal prompts

Autostart on Login

Vocalinux uses the Linux desktop standard for autostart:

  • Mechanism: XDG autostart desktop entry (vocalinux.desktop)
  • Path: $XDG_CONFIG_HOME/autostart/ or ~/.config/autostart/ (fallback)
  • Launch mode: Starts as a regular user desktop app in your graphical session
  • Not used: No systemd unit/service is created by Vocalinux for autostart

How to enable/disable:

  • First-run welcome dialog
  • Tray menu: Start on Login
  • Settings dialog: Start on Login

Compatibility notes:

  • Works on mainstream desktop environments (GNOME, KDE, Xfce, Cinnamon, MATE, LXQt)
  • On minimal/custom window-manager sessions, an autostart handler may be required (for example DE-specific startup hooks or tools like dex)

⚙️ Configuration

Configuration is stored in ~/.config/vocalinux/config.json:

{
  "speech_recognition": {
    "engine": "whisper_cpp",
    "model_size": "tiny",
    "vad_sensitivity": 3,
    "silence_timeout": 2.0
  }
}

For whisper.cpp, model_size may be a size such as tiny or an exact ggml model ID such as medium.en-q5_0 or large-v3-turbo. You can also configure this through the graphical Settings dialog, where whisper.cpp models are split into Model Size and Specialization controls. Unused leftover downloads can be deleted from Unused downloads on the Speech Model page (expand the section, then delete one model at a time).

Neural Voice Activity Detection

Vocalinux ships with a Silero VAD model and uses it automatically when onnxruntime is available. The official installer attempts to install this support automatically. Without it, recording falls back to the simpler amplitude-threshold VAD.

For manual or PyPI installs, enable neural VAD with:

pip install "vocalinux[vad]"

Restart Vocalinux after install. The Recognition tab in Settings shows which backend is active. The same vad_sensitivity (1-5) works for both -- it's mapped to a Silero probability threshold internally (1 = 0.8, 5 = 0.3).

🔧 Development Setup

# Clone and install in dev mode
git clone https://github.com/VocaHQ/vocalinux.git
cd vocalinux
./install.sh --dev

# Activate environment
source venv/bin/activate

# Run tests
pytest

# Run from source with debug
python -m vocalinux.main --debug

📁 Project Structure

vocalinux/
├── src/vocalinux/                 # Main application code
│   ├── speech_recognition/        # Speech recognition engines (VOSK, Whisper, whisper.cpp)
│   │   └── recognition_manager.py # Unified engine interface
│   ├── text_injection/            # Text injection (X11/Wayland)
│   ├── ui/                        # GTK UI components
│   └── utils/                     # Utility functions
│       ├── whispercpp_model_info.py   # whisper.cpp model metadata & hardware detection
│       └── vosk_model_info.py         # VOSK model metadata
├── tests/                         # Test suite
├── scripts/                       # Development utilities
│   └── generate_sounds.py         # Sound generation script
├── resources/                     # Icons and sounds
├── docs/                          # Documentation
└── web/                           # Website source

📖 Documentation

Repository mirrors

GitHub is the primary forge for issues, pull requests, CI, and releases.

Role URL
Primary https://github.com/VocaHQ/vocalinux
Read-only mirror (Codeberg) https://codeberg.org/jatinkrmalik/vocalinux

The Codeberg copy is a read-only source backup. Open issues and PRs on GitHub only.

🔊 Sound Customization

Vocalinux uses smooth, pleasant gliding tones for audio feedback:

  • Start: Ascending F4→A4 (0.6s) - positive, uplifting
  • Stop: Descending A4→F4 (0.6s) - resolves completion
  • Error: Lower descending E4→C4 (0.7s) - gentle but noticeable

All sounds use pure sine waves with smoothstep interpolation for buttery smooth pitch transitions - perfect for headphone use!

Regenerate Sounds

To modify or regenerate the notification sounds:

python scripts/generate_sounds.py

This script generates all three sounds using the same smooth glide algorithm. You can edit the frequencies, durations, and amplitudes in the script to customize the sounds to your preference.

🗺️ Roadmap

  • Custom icon design ✅
  • Graphical settings dialog ✅
  • Whisper AI support ✅
  • Multi-language support (FR, DE, RU) ✅
  • whisper.cpp integration (default engine) ✅
  • Vulkan GPU support ✅
  • In-app update mechanism ✅
  • Wayland support via IBus ✅
  • Flatpak packaging ✅ (manifest ships; not on Flathub — see #167)
  • Application-specific commands
  • Debian/Ubuntu package (.deb)
  • Voice command customization

🌐 The Voca Ecosystem

Vocalinux is part of VocaHQ. On-device speech-to-text first, one app per platform. Optional VocaGateway is self-hosted and not on-device.

Platform Project Website GitHub Status
🐧 Linux VocaLinux vocalinux.com VocaHQ/vocalinux ✅ Available now (v0.16.2)
🍎 macOS VocaMac vocamac.com VocaHQ/vocamac 🚀 Beta (v0.9.0)
🪟 Windows VocaWin vocawin.com VocaHQ/vocawin 🚀 Unsigned beta (v0.1.0-beta.1)
📱 Phone VocaPhone vocaphone.vocahq.com VocaHQ/vocaphone 🚀 Android beta / iOS TestFlight
🖧 Gateway VocaGateway vocagateway.vocahq.com VocaHQ/vocagateway 🧪 Beta · optional · not on-device

VocaWin is unsigned. SmartScreen may warn about an unknown publisher. It is not a Microsoft Store ship.

Each platform uses native technologies. The shared bar is on-device first; VocaGateway is optional self-hosted compute and is not on-device.

Talk to us: Discord · X @vocahq · hello@vocahq.com

🤝 Contributing

We welcome contributions! Whether it's bug reports, feature requests, or code contributions, please check out our Contributing Guide.

Contributors

Thanks to everyone who has contributed to Vocalinux! 🙌

⭐ Support

If you find Vocalinux useful, please consider:

  • ⭐ Starring this repository
  • 🐛 Reporting bugs you encounter
  • 📖 Improving documentation
  • 🔀 Contributing code

📜 License

This project is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0), aligning with the other VocaHQ distribution projects (VocaMac, VocaPhone, VocaGateway).

You may use, study, modify, and redistribute the software under AGPL-3.0. If you run a modified version as a network service, AGPL also requires that you make the corresponding source available.

Star Chart

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Description
Free, offline voice dictation for Void Linux and niri. Vulkan GPU acceleration, signed xbps repository.
Readme AGPL-3.0
35 MiB
v0.19.1
Latest
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