DocumentCode :
3576767
Title :
Deriving the relationship between user satisfaction on engine sounds and affective variable sets based on classification algorithms
Author :
Kim, W.J. ; Kim, G.W. ; Lee, Y.S. ; Yun, M.H.
Author_Institution :
Dept. of Ind. Eng., Seoul Nat. Univ., Seoul, South Korea
fYear :
2014
Firstpage :
1310
Lastpage :
1313
Abstract :
This study aims to extract the most relevant set consisted of affective variables to the level of user satisfaction on engine sounds using classification algorithm. The affective variables for engine sounds were defined by three axes, and two classification algorithms were used to determine the prediction accuracy for those affective axes. The study was consisted of three phases: 1) extracting sets of affective variables and the level of satisfaction on engine sounds, 2) preprocessing of engine sounds and experiment design, and 3) analysis of the most relevant sets of affective variables to user satisfaction. As a result, PA (Powerful-Affective) variable set showed the highest prediction accuracy of user satisfaction compared to other sets. Predicting the level of satisfaction based on classification algorithm could help to generalize the relationship between user satisfaction and affective variables more easily, beyond the limitation with a small size of subjects.
Keywords :
acoustic noise; acoustic signal processing; design of experiments; engines; signal classification; PA; affective axes; affective variable sets extraction; classification algorithm; engine sounds preprocessing; engine sounds satisfaction level; experiment design; powerful-affective variable set; prediction accuracy; user satisfaction; Accuracy; Classification algorithms; Engines; Logistics; Neurons; Prediction algorithms; Vehicles; Emotion prediction; classification algorithm; engine sounds; product sounds; user satisfaction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Engineering and Engineering Management (IEEM), 2014 IEEE International Conference on
Type :
conf
DOI :
10.1109/IEEM.2014.7058850
Filename :
7058850
Link To Document :
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