I've been working on a karaoke app called Nightingale. You point it at your music folder and it turns your songs into karaoke - separates vocals from instrumentals, generates word-level synced lyrics, and lets you sing with highlighted lyrics and pitch scoring. Works with video files too.

Everything runs locally on your machine, nothing gets uploaded. No accounts, no subscriptions, no telemetry.

It ships as a single binary for Linux, macOS, and Windows. On first launch it sets up its own isolated Python environment and downloads the ML models it needs - no manual installation of dependencies required.

My two biggest drivers for the creation of this were:

    The lack of karaoke coverage for niche, avant-garde, and local tracks.

    Nostalgia for the good old cheesy karaoke backgrounds with flowing rivers, city panoramas, etc.

Some highlights:

    Stem separation using the UVR Karaoke model (preserves backing vocals) or Demucs

    Automatic lyrics via WhisperX transcription, or fetched from LRCLIB when available

    Pitch scoring with player profiles and scoreboards

    Gamepad support and TV-friendly UI scaling for party setups

    GPU acceleration on NVIDIA (CUDA) and Apple Silicon (CoreML/MPS)

    Built with Rust and the Bevy engine

The whole stack is open source. No premium tier, no "open core" - just the app.

Feedback and contributions welcome.

  - Needs a way to skip for-/backwards during playback to validate the result
  - Sentences seem to be recognized (first letter has uppercasing), but periods aren't added
  - Needs an option to edit results from the track analysis

Open source, local and passion driven. The kind of news that make me believes in humanity again. Thank you, can't wait to try it this week-end !

I think you nailed it. Does it support pitch/tempo controls?

>app that works with any song on your computer

Impressive, very nice. Now let's see my death metal collection.

Just joking! Very nice, thanks for open-sourcing it.

This looks amazing! looking forward to test it on the weekend. Does it work well on a raspberry pi with 4 gigs of ram?

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