AI is making whole categories of projects viable that simply weren't before. Not because they were technically impossible, but because they were too time-consuming for a niche audience to justify the effort.

Thanks for the cool project! (testing now)

How come this is trying to install its own vendored dependencies, including executable binaries, instead of checking for what's already installed? That approach can lead to both security and performance issues.

Edit: the Python download isn't failing, but rather the application itself is looking for the executable interpreter in `lib` rather than `bin` once the download completes. I built the release tarball in the git repo, and I'm pretty amazed that such a basic error could make it into release code.

Further edit: I tried using the build script in the tarball rather than just doing a `cargo build -r`, and it started trying to install Docker containers! Docker to build a desktop application! What is going on here?

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.

    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

Feedback and contributions welcome.

The homepage still exists, but it looks like many of the other pages like the blog and wiki are long gone. It hasn't been active in probably over a decade.

https://getnightingale.com/

I've worked on a small toy project with a similar purpose in the past [1], though it's not nearly as polished as yours, and I've made some questionable decisions here and there.

I have questions about pitch tracking. It seems you do track the pitch for scoring, and there's a line at the top of the screen that seems related but that I can't figure out. For my use case, an important feature of karaoke apps is displaying how "high" the next note should be sung, or at least some hints. Is it something your app can do and I just haven't figured it out? Or would it be a feature request?

[1] https://github.com/eckter/karaoke_helper

Would it be possible to process songs on one device, and then use the result in another, or even multiple? Or would it be possible to run as separate server / client?

I ask mainly because the device I connect to my TV is definitely not the most powerful one, so it would be nice if I can preprocess the songs elsewhere.

A couple of immediate small pieces of feedback:

* The colour scheme on the queue/nn% buttons is really low contrast - white on pale yellow is very hard to read

* the 'models' button (bottom left) - I assumed this would give me details about which models are available, and the sizes, but instead deleted the downloaded models without warning. Maybe add a 'are you sure you want to...' check?

[1] https://www.karafun.com/

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

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

https://www.yarg.in

https://www.enchor.us/?&hasVocals=true

We already do this for ingesting podcasts and cutting their clips with text being highlighted as people speak. AssemblyAI also supports speaker diarization.

For videos recorded using our own livestreaming studio, we can bypass all this by using Web STT and TTS APIs resulting in perfect timing and diarization without the need for server side models.

ML has come a long way but I have yet to encounter anything that does this reliably with speech, never mind song lyrics.

> works with any song on your computer

I'd be shocked if this is true.