SPS SLTC/AASP TC Webinar: Physics-Informed Machine Learning in Sound Field Estimation: Fundamentals, State of the Art, and Challenges
Date: 6 June 2025
Time: 9:00 AM ET (New York Time)
Presenter(s): Dr. Shoichi Koyama, Dr. Mirco Pezzoli
Abstract
Sound field estimation, also referred to as sound field reconstruction, capturing, and interpolation, is a fundamental problem in acoustic signal processing that aims to reconstruct a spatial acoustic field from a discrete set of microphone measurements. Its wide range of applications includes the visualization/auralization of an acoustic field, spatial audio reproduction using a loudspeaker array or headphones, and active noise cancellation in a spatial region. Classical techniques were based solely on physical acoustics, but in recent years, there has been progress in combining them with more advanced signal processing and machine learning techniques. In particular, learning-based techniques using neural networks enable adaptation to the acoustic environment and improve accuracy when the number of available microphones is limited, and they are attracting attention as physics-informed machine learning (PIML).
Biography
Shoichi Koyama received the B.E., M.S, and Ph.D. degrees from the University of Tokyo, Tokyo, Japan, in 2007, 2009, and 2014, respectively.
He is currently an Associate Professor at the National Institute of Informatics (NII), Tokyo, Japan. Prior to joining NII, he was a Researcher at Nippon Telegraph and Telephone Corporation (2009-2014), and Research Associate (2014-2018) and Lecturer (2018-2023) at the University of Tokyo, Tokyo, Japan. He was also a Visiting Researcher at Paris Diderot University (Paris 7), Paris, France (2016-2018), and a Visiting Associate Professor at Tohoku University, Miyagi, Japan (2020-2023).
Mirco Pezzoli received the M.S. in computer engineering (cum laude) and the Ph.D. in information technology from Politecnico di Milano (PoliMi), Milan, Italy, in 2017 & 2021 respectviley, focusing on spatial audio and sound field reconstruction for extended audio reality.
He joined PoliMi’s Department of Electronics, Information, and Bioengineering in 2023 as a junior assistant professor, contributing to the FUNMedia project within the Italian RESTART foundation. His research spans machine learning and model-based audio processing, focusing on analyzing acoustics of environments and musical instruments, aiming to develop next-generation immersive audio.
