AI cover song platforms, How to address issues related to copyright, legal, and ethical concerns?

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When github release?

Realistically? Never. Grok-1 weights were released because it was quite bad compared to open source and closed models. Now that they have a competitive model, they won't give it away.

> Now that they have a competitive model, they won't give it away.

Lamma 3.1 is competitive.

X is not Meta.

At this point, I'm conflicted. The lyrics testing went well for me, but I'm not proficient in chords. Are the chord results really that poor? I wonder if I can use it to play my favorite songs in real life.

I play guitar/piano, and I concur that they’re not great. I tried “Vagabond (acoustic)” by Wolfmother. I figured it would have an easier time because it’s just a vocal and an acoustic guitar. Some of the notes in the tabs are right, but the melody is too simplistic. All of the embellishments are also missing. It’s interesting how the mile-high view isn’t so bad though. If I sat down to figure out the notes for a track no tabs exist for, this might look like a rough approximation of what I’d start with.

I tried a few songs and uploaded one of my favorite songs. The lyrics recognition result was excellent, but there were a few instances where some words were missing or incorrect. It would be great if there could be an option to edit the lyrics.

We are in the process of adding the lyrics editing feature, as well as chord and rhythm types. It will be released soon.

Data sourced from YouTube, which may be helpful for singing or playing the guitar.

Get chords, beats, lyrics, melody, and tabs for any song.

Based on our current tests, our algorithm shows significantly higher accuracy and robustness compared to traditional digital signal algorithms such as PEF, NCF, YIN, HPS, etc. Our team is working diligently, and we will release benchmark test data and results in the near future.

That's pretty nice. Do you have any idea how it does it?

Thank you for providing error feedback. We will work hard to address it. Currently, the model-related data is relatively large, which may be related to network speed.

I got the same error on Ubuntu/GNOME/Firefox. On Chrome, I don't get an error and I'm correctly prompted for microphone access, but if I grant permission, it does not seem to pick anything up (I've used my mic successfully with other web apps).

CREPE generally has high latency and error rates in instrument pitch recognition, especially for guitar instruments. Our team will release benchmark test data and results later.

High latency - agreed but it depends on whether a GPU is available or not. If it is then theoretically CREPE could be real-time. The error rates for pitch recognition are still quite good though for the full CREPE model. I’m interested to see the data on this claim.

Thanks. I’d love to try TuneNN! Are you releasing a pretrained model? How do I run it on a wav file?

A transformer-based network model, pitch tracking for musical instruments.

The timbre of musical notes is the result of various combinations and transformations of harmonic relationships, harmonic strengths and weaknesses, instrument resonant peaks, and structural resonant peaks over time.

It utilizes the transformer-based tuneNN network model for abstract timbre modeling, supporting tuning for 12+ instrument types.

This smells like an automated summary.

It is from the submitter. I think it is intended as a submission statement.

That’s the first time I’ve seen/noticed that. I think it makes me feel better?

Not sure what you were feeling bad about, but it’s also directly from the readme, so OP just saw something cool on GitHub and posted it along with a comment with the project’s own description, which is pretty standard on HN (I think, that’s how I’ve done it at least).