Music has emerged as an important application domain for machine learning, encompassing a wide range of tasks such as music generation, music understanding, recommendation, automatic transcription, performance analysis, and interactive music systems. Recent advances in generative AI and foundation models have further accelerated research in this area, leading to rapid progress in both academic and industrial settings. Despite these developments, music-related research remains relatively underrepresented at general machine learning conferences compared with fields such as computer vision and natural language processing.
This workshop aims to provide a forum for researchers interested in machine learning for music and related creative applications. We welcome contributions on topics including audio and symbolic music processing, music generation, music understanding, multimodal learning, computational creativity, interactive music systems, and applications of foundation models to music. Through technical presentations and discussions, the workshop seeks to promote knowledge exchange, foster new collaborations, and strengthen connections among researchers working at the intersection of music and machine learning, particularly within the Asia-Pacific region.
1st Asian-Pacific Music Intelligence Workshop (AMIW 2026) in conjunction with ACML 2026 (Dec 1-4, Merbourne)
Tetsuro Kitahara (a professor at Nihon University, Japan)
Satoshi Tojo (a professor at Asia University, Japan)
Tetsuro Kitahara <kitahara.tetsuro [at] nihon-u.ac.jp>