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The power of humorous audio: exploring emotion regulation in traffic congestion through EEG-based study

Authors :
Lekai Zhang
Yingfan Wang
Kailun He
Hailong Zhang
Baixi Xing
Xiaofeng Liu
Fo Hu
Source :
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2023, Iss 1, Pp 1-15 (2023)
Publication Year :
2023
Publisher :
SpringerOpen, 2023.

Abstract

Abstract Traffic congestion can lead to negative driving emotions, significantly increasing the likelihood of traffic accidents. Reducing negative driving emotions as a means to mitigate speeding, reckless overtaking, and aggressive driving behaviors is a viable approach. Among the potential methods, affective speech has been considered one of the most promising. However, research on humor-based affective speech interventions in the context of driving negative emotions is scarce, and the utilization of electroencephalogram (EEG) signals for emotion detection in humorous audio studies remains largely unexplored. Therefore, our study first designed a highly realistic experiment scenario to induce negative emotions experienced by drivers in congested traffic conditions. Subsequently, we collected drivers’ EEG signals and subjective questionnaire ratings during the driving process. By employing one-way analysis of variance (ANOVA) and t tests, we analyzed the data to validate the success of our experiment in inducing negative emotions in drivers during congested road conditions and to assess the effectiveness of humorous audio in regulating drivers’ negative emotions. The results indicated that humorous audio effectively alleviated drivers’ negative emotions in congested road conditions, with a 145.84% increase in arousal and a 93.55% increase in valence ratings compared to control conditions. However, it should be noted that humorous audio only restored drivers’ emotions to the level experienced during normal driving. Our findings offer novel insights into regulating drivers’ negative emotions during congested road conditions.

Details

Language :
English
ISSN :
16874722
Volume :
2023
Issue :
1
Database :
Directory of Open Access Journals
Journal :
EURASIP Journal on Audio, Speech, and Music Processing
Publication Type :
Academic Journal
Accession number :
edsdoj.0af44edf832c4ac59b7f79f4d695d269
Document Type :
article
Full Text :
https://doi.org/10.1186/s13636-023-00302-w