A few weeks ago, we had the pleasure of organizing the Workshop on Emerging AI Technologies for Music @AAAI in Singapore.

I’m excited to share that our workshop proceedings are now officially published in the Proceedings of Machine Learning Research!

Explore the full proceedings here: https://proceedings.mlr.press/v303/

Editors: Dorien Herremans, Keshav Bhandari, Abhinaba Roy, Ph.D., Simon Colton, Mathieu Barthet

The collection showcases a variety of exciting work in music AI, from foundation model applications to controllable generation, rhythm learning, timbre transfer, and more. Papers in the proceedings:

Editorial: Emerging AI Technologies for Music: Towards Controllable, Collaborative, and Creative Systems – Keshav Bhandari, Abhinaba Roy, Ph.D., Dorien Herremans, Simon Colton

• Prevailing Research Areas for Music AI in the Era of Foundation Models – Megan Wei, Mateusz Modrzejewski, Aswin Sivaraman, Dorien Herremans
• Low-Resource Rhythm Learning of South Asian Beat Structures: Machine Learning Approaches to Nattuvangam – Ankitha Sudarshan, Atharva Vikas Jadhav, Rohini Srihari
• Artificial Dancing Intelligence: Neural Cellular Automata for Visual Performance of Music – Carlos Mariano Salcedo, Eran Egozy
• The Circle of Fifths as Latent Geometry in Bach’s Well-Tempered Clavier – Najla Sadek, Joseph Bakarji
• Silence as Music: Controllable and Interpretable AI for Strategic Silence Placement – Gokul Srinath Seetha Ram
• Neural Codec Language Model for Controllable Timbre Transfer in Music Synthesis – Sheldon Liu, Tianyu Liu, Deepak Dalakoti, Adithya Suresh, Yueying Teng, Xuefeng Liu, Atanu Roy, Randeep Bhatia, Daniel Hatadi, Prabhjeet Ghuman
• TS-RaMIA: Membership Inference Attacks for Symbolic Music Generation Models – Yuxuan Liu, Rui Sang, Peihong Zhang, Zhixin Li, Kunyang Zhang, Shengyuan He, Ye Li, Kaiyi Xu, Shengchen Li
• Encoder-Only Transformers for Melodic Harmonization: Representation Emergence and Inference Strategies – Maximos Kaliakatsos-Papakostas, Dimos Makris, Konstantinos Soiledis, Konstantinos-Theodoros Tsamis
• Conditional Vocal Timbral Technique Conversion via Embedding-Guided Dual Attribute Modulation – Ting-Chao Hsu, Yi-Hsuan Yang
• A Novel Diffusion Model Based Approach for Sleep Therapeutic Music Generation – Timo Hromadka, Kevin Monteiro, Sam Nallaperuma
• Investigating Timbre Representations in CLAP Across Modalities via Perturbations – Devyani Hebbar, Brian McFee
• SingingSDS: A Singing-Capable Spoken Dialogue System for Conversational Roleplay Applications – Jionghao Han, Jiatong Shi, Masao Someki, Yuxun Tang, Lan Liu, Yiwen Zhao, Wenhao Feng, Shinji Watanabe
• Postscript on the Musics of Control – Yinuo Chen
• LLMs can read music, but struggle to hear it. An evaluation of core music perception tasks – Brandon James Carone, Iran R. Roman, Pablo Ripollés

This collection represents an exciting step forward in making music AI systems more controllable, collaborative, and creative.