Listen to an NP-Complete Problem

In plain words

Listen to an NP-Complete Problem is a GitHub-based project that transforms computational problems into audio. It takes NP-Complete problems—a class of notoriously difficult computational challenges—and converts them into sound, making abstract computer science concepts accessible through a different sensory medium. The project is designed for computer science enthusiasts, students, and curious listeners interested in exploring the intersection of mathematics, computation, and music.

written from the facts on this page · September 2026

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  An algorithmic audio landscape2024 · ambient.garden · ▲193

  This is an web audio experiment I've been wanting to do for a long time. Basically an ambient music composition, but all the sound elements are laid out in space, and that musical space can be explored freely. It's definitely inspired by in-world music that sometimes appears in games. I basically took that concept, keeping the music aspect, and dropping the entire "game" aspect. I also turned it into a more "traditional" non-interactive album, but since I started with code, why not program the whole thing? Had a blast making the entire album from code, the complete source for the album is…

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  I generated 70k audiobooks with OpenAI Text-to-Speech2024 · listenly.io · ▲140

  Hey HN. I’m Ivan, hacker from Ukraine. For about a year, I was working on Listenly — an app to listen to text content with OpenAI's natural-sounding text-to-speech model. At some moment, I realized that it would be cool to take all the public domain e-books and create audio versions for them. So I did it... kind-of. It would cost an immense amount of money to generate all the audio right away (OpenAI TTS costs approximately $0.84/hour of audio; 11labs, for comparison, is 10 times more expensive). So, I took a more gradual approach. I took all the metadata from the Project Gutenberg…

• IM
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• FA
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  Hi all, I've spent some time working on music demixing or music source separation algorithms, which take in a mixed song and output estimates of isolated components (e.g. vocals, drums, bass, other). I took a popular PyTorch model with good performance (Open-Unmix, UMX-L weights), reimplemented the inference steps in C++, and compiled it to WebAssembly for a free client-side music demixer.

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• TA
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