News

A paper co-authored by AI and Music (AIM) Centre for Doctoral Training PhD student Ben Hayes with supervisors George Fazekas and Charis Saitis received the best student paper award at the 26th International Society for Music Information Retrieval Conference, ISMIR 2025 in Daejeon, Korea. The conference is a flagship conference in the field of Music Informatics. The paper addresses the challenging and ill-posed problem of estimating audio synthesiser parameters given sound examples, where multiple parameter configurations can produce identical sounds due to intrinsic symmetries in synthesiser design. By explicitly modelling these symmetries, particularly permutation invariance across repeated components like oscillators and filters using permutation equivariant continuous normalising flows, the method outperforms both regression-based approaches and symmetry-naive generative models on both synthetic tasks and a real-world synthesiser.

You can read the paper "Audio Synthesizer Inversion in Symmetric Parameter Spaces With Approximately Equivariant Flow Matching" on the conference website.

The AIM Centre for Doctoral Training in Artificial Intelligence and Music is funded by RCUK. Based at Queen Mary University of London, AIM students undertake a four year PhD focused on developing cutting-edge research in collaboration with our industry partners.