This article surveys some new directions in algorithmic composition, with a special focus on the mass scale of content generation now within reach. Interest in algorithmic composition has recently flourished, including a fashion for deep learning, and commercial offshoots in apps and browser software. Whilst there is much to be excited about in recent developments, we critically survey some current directions, and likely future initiatives, of the field. In particular, the influence of and potential within music information retrieval research is highlighted, corresponding to attempts to bridge between audio machine listening and large corpus training for algorithmic composition. The scenario of mass generation is further considered, including a practical experiment in creating a billion melody data set with accompanying source code.
algorithmic composition, machine listening, state space, perceptual space, data set
How to CiteCollins N. (2018) ““… there is no reason why it should ever stop”: Large-scale algorithmic composition”, Journal of Creative Music Systems. 3(1). doi: https://doi.org/10.5920/jcms.525