Automatic Multi-track Mixing Using Linear Dynamical Systems

Over the past several decades music production has evolved from something that was only possible with multiroom, multi-million dollar studios into the province of the average person’s living room. New tools for digital production have revolutionized the way we consume and interact with music on a daily basis. We propose a system based on a structured audio framework that can generate a basic mix-down of a set of multi-track audio files using parameters learned through supervised machine learning. Given the new surge of mobile content consumption, we extend this system to operate on a mobile device as an initial measure towards an integrated interactive mixing platform for multi-track music.