Automatic Driver Sleepiness Detection using Wrapper-Based Acoustic Between-Groups, Within-Groups, and Individual Feature Selection

Dara Pir, Theodore Brown, Jarek Krajewski

2017

Abstract

This paper presents performance results, time complexities, and feature reduction aspects of three wrapper-based acoustic feature selection methods used for automatic sleepiness detection: Between-Groups Feature Selection (BGFS), Within-Groups Feature Selection (WGFS), and Individual Feature Selection (IFS) methods. Furthermore, two different methods are introduced for evaluating system performances. Our systems employ Interspeech 2011 Sleepiness Sub-Challenge’s “Sleepy Language Corpus” (SLC). The two tasks of the wrapper-based method, the feature subset evaluation and the feature space search, are performed by the Support Vector Machine classifier and a fast variant of the Best Incremental Ranked Subset algorithm, respectively. BGFS considers the feature space in Low Level Descriptor (LLD) groups, an acoustically meaningful division, allowing for significant reduction in time complexity of the computationally costly wrapper search cycles. WGFS considers the feature space within each LLD and generates the feature subset comprised of the best performing individual features among all LLDs. IFS regards the feature space individually. The best classification performance is obtained by BGFS which also achieves improvement over the Sub-Challenge baseline on the SLC test data.

Paper Citation

in Harvard Style

Pir D., Brown T. and Krajewski J. (2017). Automatic Driver Sleepiness Detection using Wrapper-Based Acoustic Between-Groups, Within-Groups, and Individual Feature Selection . In Proceedings of the 3rd International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-242-4, pages 196-202. DOI: 10.5220/0006294501960202

in Bibtex Style

@conference{vehits17,
author={Dara Pir and Theodore Brown and Jarek Krajewski},
title={Automatic Driver Sleepiness Detection using Wrapper-Based Acoustic Between-Groups, Within-Groups, and Individual Feature Selection},
booktitle={Proceedings of the 3rd International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2017},
pages={196-202},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006294501960202},
isbn={978-989-758-242-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Automatic Driver Sleepiness Detection using Wrapper-Based Acoustic Between-Groups, Within-Groups, and Individual Feature Selection
SN - 978-989-758-242-4
AU - Pir D.
AU - Brown T.
AU - Krajewski J.
PY - 2017
SP - 196
EP - 202
DO - 10.5220/0006294501960202