(e)met: Human-machine Interactive Composition Using Machine Learning
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.