A non-uniform subband approach to speech-based cognitive load classification

Authors:
Phu Ngoc Le;Eliathamby Ambikairajah;Eric H. C. Choi;Julien Epps
Affiliations:
School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney, NSW, Australia and ATP Research Laboratory, National ICT Australia, Eveleigh, Australia;School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney, NSW, Australia and ATP Research Laboratory, National ICT Australia, Eveleigh, Australia;ATP Research Laboratory, National ICT Australia, Eveleigh, Australia;School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney, NSW, Australia and ATP Research Laboratory, National ICT Australia, Eveleigh, Australia
Venue:
ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
Year:
2009

Citing 6
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Abstract

Speech has recently been recognized as an attractive method for the measurement of cognitive load. Current speech-based cognitive load measurement systems utilize acoustic features derived from auditory-motivated frequency scales. This paper aims to investigate the distribution of speech information specific to cognitive load discrimination as a function of frequency. We found that this distribution is neither uniform nor very similar to the Mel auditory scale and based on our experiments, we propose a novel non-uniform filterbank for acoustic feature extraction to classify cognitive load. Experimental results showed that the use of the proposed filterbank provided a relative improvement of about 10%, compared with the classification accuracy of the traditional cognitive load classification system based on a Melscale filterbank.