I Open-Sourced Eve, a 24-Hour Recording and Real-Time Transcription Tool
I kept looking for a recorder that could run continuously for meetings, quick discussions, and random ideas. After trying many tools, I found plenty of short-session recorders, but long continuous recording was either unstable or painful to organize later.
So I built my own tool, Eve (eavesdropper). It is a long-session recorder that runs on macOS, Windows, and Linux. Eve uses your computer microphone for 24-hour nonstop recording, then converts speech to text with local compute. By default it uses Qwen3-ASR for real-time recognition and VAD to filter silent parts. The goal is simple: keep recording stable and make content searchable.
Daily report generation example:
If you want to try it first, go to GitHub and follow the README:
👉 https://github.com/nexmoe/eve
uv sync + uv run eve will start it. The repository includes full parameters and usage details.
If this tool helps you, please give it a star.
Key Features
- Runs on macOS, Windows, and Linux
- Uses your computer microphone for 24-hour nonstop recording
- Splits recording into WAV segments automatically for easier playback and management
- Uses local compute for speech-to-text and writes matching JSON transcripts during recording
- Filters silent parts with VAD and processes only speech
- Can auto-switch to the currently active microphone
- You can disable ASR, record first, and transcribe in batch later
- Output text can be sent directly to LLMs for summaries, Q and A, and task extraction
Demo
The core of the OneDrive workflow is placing the Eve output directory inside your local OneDrive sync folder.
Recorded audio files and transcript files are written locally first, then OneDrive automatically syncs them to the cloud for persistent storage.
This helps you recover historical recordings and transcripts even after accidental local deletion, disk failure, system reinstall, or device replacement.
Example of audio and transcript files inside OneDrive:
Why I built this
I want to preserve original voice data first, not only final summaries.
Models keep improving. Audio that transcribes poorly today can often be processed better later.
So Eve was never about pretty summaries first. It is about stable recording first.
I plan to add more features over time, for example:
- Better keyword search and timeline navigation
- Automated daily report and meeting note workflows
- More robust device switching strategy and error recovery
- Better cloud archive and sync experience
The project is already open-sourced on GitHub.
If you are interested in this direction, feel free to open issues or pull requests and improve it together.