Title :
Feature selection and classification of speech under long-term stress
Author :
Bin Hu; Zhenyu Liu; Lihua Yan; Tianyang Wang; Fei Liu; Xiaoyu Li; Huanyu Kang
Author_Institution :
Ubiquitous Awareness and Intelligent Solutions Lab, Lanzhou University, China
Abstract :
Many studies were proposed to discuss acoustic correlates of stress in recent years. Considering some inconsistent experiment results, we supposed that stress should be categorized into long-term and short-term stress in this topic, and the trend of short-term stress induced by workload may be affected by long-term stress. This study contains three parts: first, we proposed an acoustic feature set chosen by feature selection, which can be considered as a measurement of the level of long-term stress; second, we showed that this set is immune to short-term stress in stress classification tests; finally, we observed some particular voice features mentioned in previous researches in our experiment and the results may imply that short-term stress trend is in connection with the level of long-term stress. In short, long-term and shot-term stress should be discussed separately in future researches for clear and explicit conclusions.
Keywords :
"Support vector machines","Niobium","Atmospheric measurements","Particle measurements","Jitter","Education","Market research"
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2015 IEEE International Conference on
DOI :
10.1109/BIBM.2015.7359804