RoboJam is a machine-learning system for generating music that assists users of a touchscreen music app by performing responses to their short improvisations. This system uses a recurrent artificial neural network to generate sequences of touchscreen interactions and absolute timings, rather than high-level musical notes. To accomplish this, RoboJam’s network uses a mixture density layer to predict appropriate touch interaction locations in space and time. In this paper, we describe the design and implementation of RoboJam’s network and how it has been integrated into a touchscreen music app. A preliminary evaluation analyses the system in terms of training, musical generation and user interaction.
CITATION STYLE
Martin, C. P., & Torresen, J. (2018). RoboJam: A musical mixture density network for collaborative touchscreen interaction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10783 LNCS, pp. 161–176). Springer Verlag. https://doi.org/10.1007/978-3-319-77583-8_11
Mendeley helps you to discover research relevant for your work.