Abstract
Performing tasks quickly and accurately in dynamic and intense environments is critical, such as supervising a remotely piloted aircraft; however, these environments contain periods of low and high workload, which can decrease task performance. A system capable of intelligently adapting its interaction modality based on the human’s workload state may mitigate these undesirable workload states: underload and overload. Such a system requires mechanisms to determine accurately the human’s overall workload state and each workload component state (i.e., cognitive, physical, visual, speech, and auditory) in order to understand the current workload state’s underlying cause effectively. Existing work estimates multiple workload components, but no method estimates speech workload. This manuscript presents an algorithm for accurately estimating a human’s speech workload level using methods suitable for real-time workload assessment. The algorithm is an essential component to future adaptive human-machine interfaces.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
