Dabri is a Linux speech-to-text application that converts spoken words into text for editors, browsers, IDEs and other desktop applications.
The application operates as a background service rather than a dedicated document editor. Users can dictate text directly into the active window or copy transcriptions to the clipboard. All speech recognition takes place locally, without sending recorded audio to an external service.
Dabri combines desktop integration with command-line functionality. Its architecture makes it suitable for everyday voice typing as well as scripting and automation, where transcribed speech can be passed to other applications or used to trigger actions.
This is free and open source software.
Key Features
- Offline speech recognition using Whisper and NVIDIA Parakeet models.
- Choose between several Whisper models offering different balances of speed, memory consumption and accuracy.
- Parakeet supports 25 European languages and automatically identifies the spoken language.
- Vulkan GPU acceleration for supported speech recognition workloads, with CPU fallback.
- Configurable global keyboard shortcuts with toggle and push-to-talk recording modes.
- System tray integration for managing recording, models and application settings.
- Automatic text insertion under X11 and Wayland using desktop-specific input methods.
- Clipboard fallback when direct text insertion is unavailable.
- Audio recording through ALSA or PulseAudio/PipeWire using supported capture tools.
- Desktop notifications for recording status and hotkey errors.
- Command-line interface for controlling recording, retrieving transcripts and managing recognition models.
- JSON output for integration with shell scripts and automation workflows.
- Unix socket IPC and an optional WebSocket server for external application integration.
- Integration with GNOME, KDE Plasma and tiling window managers.
Website: github.com/AshBuk/dabri
Support:
Developer: Asher Buk
License: MIT License
Dabri is written in Go. Learn Go with our recommended free books and free tutorials.
Related Software
| Speech Recognition Tools | |
|---|---|
| Whisper | Automatic speech recognition (system trained on 680,000 hours of data |
| whisper.cpp | Run Whisper locally with fast, efficient C/C++ speech recognition |
| Flashlight | Fast, flexible machine learning library written entirely in C++. |
| sherpa-onnx | Offline speech recognition for many platforms and languages |
| Kaldi | C++ toolkit designed for speech recognition researchers. |
| FunASR | Versatile speech recognition toolkit for real-world audio |
| faster-whisper | Faster Whisper transcription with reduced memory use |
| SpeechBrain | All-in-one conversational AI toolkit based on PyTorch |
| Handy | Offline speech-to-text application |
| ESPnet | End-to-End speech processing toolkit |
| PocketSphinx | Lightweight speech recognition for embedded and mobile use |
| deepspeech.pytorch | Implementation of DeepSpeech2 using Baidu Warp-CTC. |
| Epicenter | Transcription application with global speech-to-text functionality |
| Julius | Two-pass large vocabulary continuous speech recognition engine |
| Speech Note | Write notes, transcribe speech, translate text and read content aloud |
| aTrain | Private local transcription of recorded speech through a polished GUI |
| hyprwhspr | Native speech-to-text designed for Arch / Omarchy |
| Vocalinux | Local voice dictation through a clean desktop interface |
| ostt | Open Speech-to-Text |
| Simon | Flexible speech recognition software |
Read our verdict in the software roundup.
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