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An epitomization of stress recognition from speech signal

Publication Type : Journal Article

Publisher : International Journal of Engineering and Technology(UAE)

Source : International Journal of Engineering and Technology(UAE), Science Publishing Corporation Inc, Volume 7, Number 2 Special Issue 27, p.61-68 (2018)

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052906874&partnerID=40&md5=4cad556414cf7ecfc4dddbd5c122ba07

Campus : Bengaluru

School : School of Engineering

Department : Electronics and Communication

Year : 2018

Abstract : pThe Detection of stress from speech signal is gaining large attention recently. The emergence of new methods and techniques for feature extraction and classification paved the way to different solutions to detect different stress conditions using human speech and led to an in-crease in the accuracy of stress recognition. A large number of parameters are proposed for the characterization of stress in speech. Similarly numerous classifiers and machine learning algorithms are investigated for stress classification and regression. In this treatise, a recital on the commonly used databases, stress conditions, different feature extraction methods and classifiers along with some of the statistical measures as well as compensation techniques for stress detection are presented in this article. After thorough illustration of existing methodology for the task, future prospects for the work are elaborated. © 2018 Veena Narayanan et al./p

Cite this Research Publication : V. Narayanan, Lalitha, S., and Gupta, D., “An epitomization of stress recognition from speech signal”, International Journal of Engineering and Technology(UAE), vol. 7, pp. 61-68, 2018.

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