You Sound Relaxed Now - Measuring Restorative Effects from Speech Signals

HUMAN-COMPUTER INTERACTION, INTERACT 2021, PT II(2021)

引用 0|浏览3
暂无评分
摘要
The recently proposed restorative environments have the potential to restore attention and help against fatigue, but how can these effects be verified? We present a novel measurement method which can analyze participants' speech signals in a study before and after a relaxing experience. Compared to other measurements such as attention scales or response tests, speech signal analysis is both less obtrusive and more accessible. In our study, we found that certain time- and frequency-domain speech features such as short-time energy and Mel Frequency Cepstral Coefficients (MFCC) are correlated with the attentional capacity measured by traditional ratings. We thus argue that speech signal analysis can provide a valid measure for attention and its restoration. We describe a practically feasible method for such a speech signal analysis along with some preliminary results.
更多
查看译文
关键词
Speech feature analysis, Attention measurement, Restoration
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要