DocumentCode
3100026
Title
Research of detecting fatigue from speech by PNN
Author
Zhang, Xiao-Jun ; Gu, Ji-Hua ; Tao, Zhi
Author_Institution
Dept. of Phys. Sci. & Tech., Soochow Univ., Suzhou, China
Volume
2
fYear
2010
fDate
18-19 Oct. 2010
Abstract
Fatigue is a natural phenomenon which is a kind of self-regulation and protection for human body. Detection fatigue states have positive significance for all occupations now. This paper presents a feature-based parameters and the probabilistic neural network (PNN) speech recognition model to detect fatigue. Through training at different times of voice samples as the voice sources and establishing a comprehensive identification system. Experimental results show that this way can reflect the degree of fatigue. MFCC parameters is superior to LPCC.
Keywords
cepstral analysis; fatigue; feature extraction; neural nets; speech recognition; PNN; comprehensive identification system; melfrequency cepstral coefficient; probabilistic neural network; speech fatigue detection; speech recognition model; voice sampling; Mel frequency cepstral coefficient; Fatique; LPCC; MFCC; PNN; Speech;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Networking and Automation (ICINA), 2010 International Conference on
Conference_Location
Kunming
Print_ISBN
978-1-4244-8104-0
Electronic_ISBN
978-1-4244-8106-4
Type
conf
DOI
10.1109/ICINA.2010.5636509
Filename
5636509
Link To Document