Di Guo-Qing, Wu Si-Xia
Institute of Environmental Pollution and Control Technology, Zhejiang University, Number 866 Yuhangtang Road, Hangzhou 310058, People's Republic of China.
J Acoust Soc Am. 2015 Aug;138(2):994-1002. doi: 10.1121/1.4927693.
This research aims to explore the feasibility of using back-propagation (BP) neural networks and electroencephalograms (EEGs) to recognize the emotional reactions induced by sound stimuli in the dimensions of pleasure and arousal, as well as compare the recognition performance of each method on these two dimensions. It could provide an aided design on choosing proper sounds to induce or regulate individuals' emotional states under specific situations for potential users at the design stage. Emotional reactions to different sound stimuli are investigated by Self-Assessment Manikin. The results of BP neural network indicate that the arousal predictions are more satisfactory than the pleasure predictions, and the recognition rates can be improved by optimizing input parameters. EEG signals induced by sound stimuli are recorded. The results show that when induced by each pleasant sound, the Average Power of Electroencephalogram of the α wave in the left frontal pole electrode is significantly lower than that in the right frontal pole electrode, while when induced by each unpleasant sound, the former is significantly higher than the latter. This finding indicates that pleasant and unpleasant sounds can be identified based on the asymmetry of the α wave between the left and right frontal pole electrodes.
本研究旨在探讨使用反向传播（BP）神经网络和脑电图（EEG）来识别声音刺激在愉悦和唤醒维度上引发的情绪反应的可行性，并比较每种方法在这两个维度上的识别性能。它可以为潜在用户在设计阶段选择合适的声音以在特定情况下诱导或调节个体情绪状态提供辅助设计。通过自评人偶研究对不同声音刺激的情绪反应。BP神经网络的结果表明，唤醒预测比愉悦预测更令人满意，并且通过优化输入参数可以提高识别率。记录声音刺激诱发的脑电信号。结果表明，当由每种愉悦声音诱发时，左额极电极处α波的脑电图平均功率显著低于右额极电极处，而当由每种不愉快声音诱发时，前者显著高于后者。这一发现表明，可以基于左右额极电极之间α波的不对称性来识别愉悦和不愉快的声音。
