Title: Machine Learning for Modeling Human Performance and Interactions
Akira Maezawa, Senior Engineer at Yamaha Corporation

 

Understanding how a human performer responds to and interacts with other musicians is crucial for developing interactive music systems. In this talk, I will present our research on modeling music performance and interaction between human performers using machine learning techniques. Additionally, I will introduce our music installations and concert events that have integrated these technologies.

 

 

Akira is a researcher in music informatics, passionate about delivering the rewarding experience of music-making to more people through technology.  He has worked on research and development of music information retrieval and audio signal processing technologies using machine learning, which is now used in various platforms like mobile apps to electronic keyboard instruments.  He has also worked on real-time music ensemble and interactive systems, which have made appearances in concert venues and interactive installations worldwide, enjoyed by thousands of musicians.He and the projects for which he has served as the tech lead have received numerous awards and honorary mentions (10+), including the Cannes Lions International Festival of Creativity's Entertainment Lions for Music (SILVER), the Information Processing Society of Japan’s Research and Engineering Award, the Yamashita Research Award and the Galaxy Award.

more info: https://www.yamaha.com/en/tech-design/research/student/akira_maezawa/

 

Activity in the frame of:

Cátedra UPF-BMAT en Inteligencia Articial y Música (TSI-100929-2023-1). Project funded by Secretaría de Estado de Digitalización e Inteligencia Artificial, and Unión Europea-Next Generation EU