@article{oai:nagoya.repo.nii.ac.jp:00012027,
 author = {Malta, Lucas and Miyajima, Chiyomi and Kitaoka, Norihide and Takeda, Kazuya},
 journal = {Intelligent Vehicles Symposium, 2009 IEEE},
 month = {Jun},
 note = {In this paper we present our latest achievements in the continuous estimation of a driver's spontaneous irritation. Experiments are conducted with data from 20 drivers, recorded under real driving conditions. While driving, participants also interact with a speech dialogue system to retrieve and play music. A fusion method is proposed to integrate information on the driving environment, driver behavior, driver's physiological state, and speech recognition results. Overall, we are able to correctly detect 80% (true positive rate) of the irritation, and, when drivers are not irritated, we only make mistakes 9% of the time (false positive rate). Results also support the relevance of gas- and brake-pedal operation as well as speech recognition results in irritation estimation.},
 pages = {573--577},
 title = {Multimodal estimation of a driver's spontaneous irritation},
 year = {2009}
}