Abstract
The research shows that subjective feelings of people, such as emotions and fatigue, can be objectively reflected by electroencephalography (EEG) physiological signals Thus, an evaluation method based on EEG, which is used to explore auditory brain cognition laws, is introduced in this study. The brain cognition laws are summarized by analyzing the EEG power topographic map under the stimulation of three kinds of automobile sound, namely, quality of comfort, powerfulness, and acceleration. Then, the EEG features of the subjects are classified through a machine learning algorithm, by which the recognition of diversified automobile sound is realized. In addition, the Kalman smoothing and minimal redundancy maximal relevance (mRMR) algorithm is used to improve the recognition accuracy. The results show that there are differences in the neural characteristics of diversified automobile sound quality, with a positive correlation between EEG energy and sound intensity. Furthermore, by using the Kalman smoothing and mRMR algorithm, recognition accuracy is improved, and the amount of calculation is reduced. The novel idea and method to explore the cognitive laws of automobile sound quality from the field of brain-computer interface technology are provided in this study.
Highlights
Methods that are applied to evaluate automobile sound quality mainly rely on the psychological feelings of people and cannot guarantee the universality of evaluation results (Tan and Tan, 2012)
Some literature has proved that the frontal area is closely related to human brain cognition (Saxe, 2006; Shamay-Tsoory and Aharon-Peretz, 2007), and there is a large proportion of energy in the frontal area under musical stimulation (Sammler et al, 2010; Di and Wu, 2015)
The objective of this research is to investigate the laws of brain cognition under the stimulation of diverse automobile sounds and propose an effective method to identify diversified automobile sounds
Summary
Methods that are applied to evaluate automobile sound quality mainly rely on the psychological feelings of people and cannot guarantee the universality of evaluation results (Tan and Tan, 2012). Semantic differentiation (Guo et al, 2017), grade score, pairing comparison (Parizet, 2002; Ellermeier et al, 2004) are commonly used for subjective evaluation. When the sound qualities with similar semantics (such as “comfort,” “powerfulness,” and “acceleration”) are designed under the dominance of sound forward design, and the traditional subjective evaluation methods are difficult to reflect the true feelings of the evaluator. It is necessary to introduce a new automobile sound quality evaluation method for evaluating the diversified automobile sound
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
