AI-assisted laughter detection software v. human coders: a new way to collect objective data about stand-up comedy performances?

Audience laughter is central to the interaction between stand-up comedians and their audiences, but systematic human coding of laughter is labour intensive. To address this challenge, this paper evaluates the performance of an AI-assisted tool that measures the laughter found in recordings of stand-up comedy performances, the StandApp Comedy App. We present a comparison of the laughs per minute data from our hand-coded study and the data produced by the app, discuss some of the current limitations of the app, and explain why, despite these limitations, we believe the application provides valua