This event is a combined open lab, talk, and live demonstration. Each 1.5 hour session is designed to showcase multi-disciplinary art making processes that utilize and engage with sensor technology. Live demonstrations will take place as well as an introduction to the history of sensor technology development at Berkeley.
The practice and theory of contextual instrument design for use in musical expression is explored. Students create new instruments and performance environments using a variety of physical interaction paradigms, programming practices, and musical processes emerging from the UC Berkeley Center for New Music and Audio Technologies (CNMAT). Building on the methodologies established in Music 158A, the course develops aesthetic, analytic and technical skills through discussion, empirical study, and collaborative engagement.
Our goal is to make a computer program that interacts with human improvising musicians to automatically co-author music in real time using machine learning. This real-time interactive system will contribute to and draw from already existing branches of study in music composition and computer science. From computer science, the system will apply techniques from Music Information Retrieval (MIR) and Machine Learning to analyze and generate musical content. Within the domain of music composition, our piece aims to develop an interactive digital framework for gesture-based music improvisation.