Title :
A study of effectiveness of speech enhancement for cognitive load classification in noisy conditions
Author :
Phu Ngoc Le;Eliathamby Ambikairajah;Tharmarajah Thiruvaran;Tuan Thanh Nguyen
Author_Institution :
School of Electrical Engineering and Telecommunications, The University of New South Wales, UNSW Sydney, NSW 2052, Australia
Abstract :
In the last decade, speech-features have been effectively utilized for estimating cognitive load level in ideal conditions where recorded speech is clean. However, in more realistic conditions, the recorded speech data is corrupted by noise. Hence, the employment of speech enhancement is essential to reduce the noise. In this paper, the effectiveness of three speech enhancement algorithms proposed in our previous studies are compared based on performance and processing time and the most suitable method is utilized to denoise the input noisy speech before feeding it to a cognitive load classification system in order to improve its performance. The results of this study indicate that the use of speech enhancement can reduce 3.0% of average relative error rate for the system under the effect of various noisy conditions.
Keywords :
"Speech","Speech enhancement","Noise measurement","Discrete cosine transforms","Chlorine","Kalman filters"
Conference_Titel :
Advanced Technologies for Communications (ATC), 2015 International Conference on
Print_ISBN :
978-1-4673-8372-1
DOI :
10.1109/ATC.2015.7388370