Formant frequencies under cognitive load: effects and classification

  • Authors:

  • Tet Fei Yap;Julien Epps;Eliathamby Ambikairajah;Eric H. C. Choi

  • Affiliations:

  • School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney, and ATP Research Laboratory, National ICT Australia, Eveleigh, NSW, Australia;School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney, and ATP Research Laboratory, National ICT Australia, Eveleigh, NSW, Australia;School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney, and ATP Research Laboratory, National ICT Australia, Eveleigh, NSW, Australia;ATP Research Laboratory, National ICT Australia, Eveleigh, NSW, Australia

  • Venue:
  • EURASIP Journal on Advances in Signal Processing - Special issue on emotion and mental state recognition from speech
  • Year:
  • 2011

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Abstract

Cognitive load measurement systems measure the mental demand experienced by human while performing a cognitive task, which is useful in monitoring and enhancing task performance. Various speech-based systems have been proposed for cognitive load classification, but the effect of cognitive load on the speech production system is still not well understood. In this work, we study formant frequencies under different load conditions and utilize formant frequency-based features for automatic cognitive load classification. We find that the slope, dispersion, and duration of vowel formant trajectories exhibit changes under different load conditions; slope and duration are found to be useful features in vowel-based classification. Additionally, 2-class and 3-class utterance-based classification results, evaluated on two different databases, show that the performance of frame-based formant features was comparable, if not better than, baseline MFCC features.