Title :
Analysis of Stress in speech using adaptive Empirical Mode Decomposition
Author :
Zhang, James Z. ; Mbitiru, Nyaga ; Tay, Peter C. ; Adams, Robert D.
Author_Institution :
Dept. of Eng. & Technol., Western Carolina Univ., Cullowhee, NC, USA
Abstract :
Stress in human speech can be detected by various methods know as Voice Stress Analysis (VSA). The detection is accomplished by measuring the frequency shift of a microtremor normally residing in the frequency range of 8 to 12 Hz when not stressed. Conventional detection methods include Fast Fourier Transform (FFT) or McQuiston-Ford algorithm. This paper presents a new method called Adaptive Empirical Mode Decomposition (AEMD) applied to voice stress detection. Because AEMD in essence is a time-frequency analysis method, it is possible to use this method for real-time voice stress detection.
Keywords :
fast Fourier transforms; speech processing; stress analysis; time-frequency analysis; McQuiston-Ford algorithm; adaptive empirical mode decomposition; conventional detection methods; fast Fourier transform; frequency 8 Hz to 12 Hz; human speech stress analysis; microtremor frequency shift; time-frequency analysis method; voice stress detection; Change detection algorithms; Delay; Fast Fourier transforms; Frequency; Human factors; Military equipment; Muscles; Psychology; Speech analysis; Stress measurement;
Conference_Titel :
Signals, Systems and Computers, 2009 Conference Record of the Forty-Third Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
978-1-4244-5825-7
DOI :
10.1109/ACSSC.2009.5469829
