Unsupervised Play: Machine Learning Toolkit for Max

Smith, Benjamin D. and Garnett, Guy E.

Proceedings of the International Conference on New Interfaces for Musical Expression

Machine learning models are useful and attractive tools for the interactive computer musician, enabling a breadth of interfaces and instruments. With current consumer hardware it becomes possible to run advanced machine learning algorithms in demanding performance situations, yet expertise remains a prominent entry barrier for most would-be users. Currently available implementations predominantly employ supervised machine learning techniques, while the adaptive, self-organizing capabilities of unsupervised models are not generally available. We present a free, new toolbox of unsupervised machine learning algorithms implemented in Max 5 to support real-time interactive music and video, aimed at the non-expert computer artist.