CoLoSS: Cognitive Load Corpus with Speech and Performance Data from a Symbol-Digit Dual-Task

Abstract

In this paper, a new corpus named CoLoSS (Cognitive Load by Speech and performance data in a Symbol-digit dual-task) is presented, which contains speech under cognitive load recorded in a learning task scenario. In order to obtain a reference for cognitive load, a dual-task approach was applied, including a visual-motor primary task that required subjects to learn abstract symbol combinations and an auditory-verbal secondary task to measure the load imposed by the primary task. We report the methodology of collecting the speech recordings, constructing the corpus and describe the properties of the data. Finally, effects of cognitive load on prosodic as well as voice quality features are investigated in conjunction with the corpus. In its current version, the corpus is available to the scientific community, e.g., for exploring the influence of cognitive load on speech or conducting experiments for speech-based cognitive load recognition.

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