Cognitive load refers to the capacity and resources used in working memory while learning – completing tasks where novel information and novel processing are required. In complex and time-critical situations, system users can experience extremely high cognitive load, which can interfere with task completion. An understanding of the users’ cognitive load will enable us to alleviate these problems by implementing strategies to adjust the system’s behavior, support, and resources needed as per their cognitive burden and help them complete the task effectively. Moreover, for complex collaborative tasks where many users have to cooperate to solve task-related problems, understanding cognitive demands can be very helpful. However, cognitive load is difficult to measure, particularly across individual users, and there is clearly room for innovation in this area.

Certain speech features have been shown to change under high levels of load and are good candidates for cognitive load indices for usability evaluation and automatic adaptation of an interface or work environment. Several speech-based user study and analysis will be presented in which we explore the behaviour of speech features in natural speech. Our other study presents a speech content analysis approach to the measurement of cognitive load which employs users’ linguistic and grammatical features of speech to determine their experienced level of cognitive load. We present the analyses of several linguistic features extracted from the speech data collected involved in highly time-critical and data-intense bushfire management tasks around Australia. Some preliminary results of relationship between cognitive load and linguistic features in collaborative work will also be presented.