Exploring how AI-based real-time transcriptions can help overcome distractions for online meeting participants

Abstract

Online meetings have become indispensable in collaborative remote work environments due to the increased remote work and globalization. Their distributed and location-agnostic nature often causes vulnerability to voluntary and involuntary distractions, which leads to a loss of engagement and context. However, working from home environments has unavoidable distractions, and natural multitasking has positive tradeoff effects that increase overall work productivity. This study investigates the impact of real-time transcriptions (i.e., full-transcripts, summaries, and keywords) as a solution to facilitate online meetings during distracting moments while still preserving multitasking behaviors. Through two rounds of controlled user studies, we demonstrate both qualitatively and quantitatively that real-time transcriptions help participants catch up with the meeting flow and reduce interference, particularly after distractions. Furthermore, we uncover additional benefits of real-time transcriptions, such as supporting content recall, and suggest design implications for future online meeting platforms to adaptively provide transcriptions based on users' specific needs and goals.