DETECTION OF STRESS IN SPEECH USING FEATURES DERIVED FROM NONLINEAR MODEL OF SPEECH PRODUCTION

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TORABI S.; ALMASGANJ F.; MOHAMMADIAN A.

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Journal: SIGNAL AND DATA PROCESSING Year:2008 | Volume:- | Issue:1 (SERIAL 9) Page(s): 85-96

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Information Journal Paper

Title

DETECTION OF STRESS IN SPEECH USING FEATURES DERIVED FROM NONLINEAR MODEL OF SPEECH PRODUCTION

Author(s)

TORABI S. | ALMASGANJ F. | MOHAMMADIAN A. | Issue Writer Certificate

Keywords

DETECTION OF STRESSQ3

DETECTION OF EMOTIONQ3

SPEECH PROCESSINGQ2

Abstract

It is well known that speech signal is affected by speaker's psychological stress. Some of the recent works have evaluated different acoustic features individually, for detecting stress in speech and among these parameters, the nonlinear feature of TEO-CB-Auto-Env is known as the best one. In this work, a new mixed feature (TEO-Pch-LFPC) is proposed and investigated for the task of stress classification, using simulated domain of SUSAS database (styles of Neutral, Angry, Loud and Lombard). The precedence of this work is that it uses more simple classifiers rather than HMM (i.e. static classifiers of KNN, LDA and SVM), and the Round Robin Method is exerted. For pair-wise classification, the proposed approach reaches 93.78% and in multi-style case, the accuracy of 70.22% is obtained.

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APA: Copy

TORABI, S., ALMASGANJ, F., & MOHAMMADIAN, A.. (2008). DETECTION OF STRESS IN SPEECH USING FEATURES DERIVED FROM NONLINEAR MODEL OF SPEECH PRODUCTION. SIGNAL AND DATA PROCESSING, -(1 (SERIAL 9)), 85-96. SID. https://sid.ir/paper/356569/en

Vancouver: Copy

TORABI S., ALMASGANJ F., MOHAMMADIAN A.. DETECTION OF STRESS IN SPEECH USING FEATURES DERIVED FROM NONLINEAR MODEL OF SPEECH PRODUCTION. SIGNAL AND DATA PROCESSING[Internet]. 2008;-(1 (SERIAL 9)):85-96. Available from: https://sid.ir/paper/356569/en

IEEE: Copy

S. TORABI, F. ALMASGANJ, and A. MOHAMMADIAN, “DETECTION OF STRESS IN SPEECH USING FEATURES DERIVED FROM NONLINEAR MODEL OF SPEECH PRODUCTION,” SIGNAL AND DATA PROCESSING, vol. -, no. 1 (SERIAL 9), pp. 85–96, 2008, [Online]. Available: https://sid.ir/paper/356569/en

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