trail mix

Cuelume. Interaction sounds for the web

Cuelume is a tiny, dependency-free library of carefully designed interaction sounds, synthesized live with Web Audio.

How Much AI Is in This Track? Quantifying the Proportion of AI-Generated Stems in Hybrid Music Mixtures

AI-generated music is increasingly used at the stem level, with producers integrating synthetic drums, basslines, or vocals alongside human-performed instruments. However, current AI music detection systems are binary, treating tracks as either fully AI or fully human. In this paper, we reformulate AI music detection as a regression problem on a continuous AI energy ratio, alpha in [0, 1]. We propose a methodology that leverages a multi-track music dataset to assemble mixtures of human-performed and AI-reconstructed stems (obtained using a neural audio codec) with known proportions of each content type. Using this approach, we first show that a CNN-based model trained on fully AI-generated or human-performed tracks, which achieves >99% accuracy as a binary detector, when faced with mixed content, yields an output that rises with the AI stems' energy contribution, acting as a noisy and miscalibrated estimator. Our analysis of the influence of different stems shows that detection sensitivity depends on the instrument and reflects its frequency content: drums and guitar carry strong codec-artifact signatures, while vocals and bass are less detectable. Based on these insights, we train a similar CNN-based model for regression of alpha, achieving MAE = 0.076 and R^2 = 0.85 on held-out mixtures from the same pipeline. These results suggest that the regression formulation is an initial promising step towards AI-music detection in realistic music production workflows.

[Music Assets] FREE Music Loop Bundle

Over 150 seamless music loops for all genres and styles of games

tsiry-sandratraina.com/music-player

An extensible music server written in Rust , single binary, zero dependency

HAIM: Human-AI Music Datasets for AI Music Production Tracking Benchmark

As generative platforms such as Suno and Udio reach human-grade audio quality, the scope of AI's utility has expanded across the entire music production workflow. Beyond simple track generation, these advancements have catalyzed the adoption of AI-driven methodologies in diverse forms. These include vocal synthesis, arrangement, and professional mastering. However, current detection research remains largely confined to a binary `AI-or-human' paradigm. It fails to reflect the realities of contemporary music production workflows. In real-world production, AI tools are increasingly used to refine or master human-produced tracks, and human engineers likewise post-process AI-generated material to ensure professional quality. Moreover, users often employ adversarial tactics to bypass AI detectors, such as applying human mastering to AI-generated tracks. This creates a grey area that a simple binary classification fails to capture. In this paper, we define and investigate ``AI Music Tracking'': the challenge of identifying specific AI integration across the multifaceted spectrum of music production. To this end, we introduce HAIM, a dataset with diverse labels for stages of music production. It is designed to isolate stages of AI intervention, including hybrid production and agent-level tracking. Our evaluation of state-of-the-art detectors reveals systemic flaws. By releasing HAIM, we propose a new benchmark that shifts the field beyond binary classification toward a granular, structured evaluation of AI music.

MANIFEST AUDIO | Creative Tools for Ableton Live

Creative Max for Live devices, MIDI tools, effects, and racks for Ableton Live. Designed for creative producers, demanding performers, and intrepid sound explorers.

@web-kits/audio

Declarative audio synthesis for the web.

GitHub - teal-fm/piper: [WIP] music platform user data scraper

[WIP] music platform user data scraper. Contribute to teal-fm/piper development by creating an account on GitHub.

Rocksky (@rocksky.app)

A decentralized music tracking and discovery platform built on @atproto.com 🎵 . Scrobble your plays, share playlists, and explore listening trends, not affiliated with @bsky.app Support the project → https://github.com/sponsors/tsirysndr

runoffgroove.com

This is the Runoff Groove, featuring do-it-yourself guitar stompbox mp3 sound clips and my notes on building one fuzz box after another. Also, schematics and articles related to effect pedals.

tsirysndr/music-player

An extensible music server written in Rust , single binary, zero dependency 🚀🎵✨

Nate Spilman

Software - urban biking - music Happy to be here. https://natespilman.tngl.io/