Abstract: A common, and arguably innate, human response when listening to music is to tap one's foot to mark the regular pulse of the beat. A more complex form of interactive synchronization occurs when listeners tap out rhythmic patterns using their fingers, hands, or even some form of improvised drumsticks. In this late-breaking demo, we explore this interaction by leveraging the style transfer capabilities of a neural audio synthesis model by training it on a drum dataset and feeding it tapped rhythm recordings at inference time. We also provide a concise and high-level overview of the results, which, in our assessment, not only justify further research but also establish an intriguing baseline for future investigations. Finally, we point out several future research directions.