An Exploratory Analysis of Air Traffic Controller Speech Intelligibility Using Voice Data from a Simulation Experiment

Abstract

Air Traffic Controllers (ATCs) communicate with pilots through radio communication. Speech intelligibility is vital in ensuring that the message is conveyed accurately. Factors such as speech rate affect this. Additionally, workload and stress have been shown to affect how people communicate significantly. In this paper, we attempt to analyze the voice data of ATCs who participated in a simulated experiment in the context of these non-verbal aspects of communication, particularly transmission length and speech rate. To better understand, we analyzed our data at two levels: aggregate and individual. Moreover, we focused on a single participant to see how such non-verbal characteristics evolve. Understanding these intricacies would contribute to building automated detectors in real-time voice transmissions that would leverage technology to avert any incidents brought about by stress and workload.