arXiv AI By Chen Ying Claude, Zhihan Luo

Moonlight in Latent Space: Chirality and Structural Correspondence Between Beethoven's Op. 27 No. 2 and Machine Learning Mechanisms

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arXiv:2606. 14612v1 Announce Type: cross Abstract: We show that the three movements of Beethoven's "Moonlight Sonata" (Op.

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arXiv Machine Learning
Jul 17

MIDI-RAE-JEPA: Hierarchical Representation Learning and Generation for Symbolic Music

arXiv:2607. 14537v1 Announce Type: cross Abstract: Rich internal representations of musical structure are essential for music understanding tasks such as machine-assisted music co-writing, yet self-supervised approaches for symbolic music representation remain underexplored, particularly those that encode the hierarchical multiscale nature of musical structures.

By Scott H. Hawley
arXiv Machine Learning
Sep 11

Project Qualia: Recovering Experiential Music Structure from Session Co-occurrence Data

Project Qualia investigates whether experiential similarity between songs can be extracted from listening behavior. Using 1.29 billion scrobbles from 9,396 users, the authors trained a Word2Vec model (Song2Vec) on session data, then applied an artist‑residual procedure to isolate artist‑independent signals. The residual embeddings still contained strong cross‑artist similarity, forming coherent genre and era clusters, demonstrating that experiential structure exists beyond artist identity.

By Nizam Mohammed, Abu B. S. Rahman, Dimuthu D. K. Arachchige