Detection of stress and emotion in speech using traditional and FFT based log energy features
In this paper, a novel system for detection of human stress and emotion in speech is proposed. The system makes use of FFT based linear short time Log Frequency Power Coefficients (LFPC) and TEO based nonlinear LFPC features in both time and frequency domains. The performance of the proposed system...
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sg-ntu-dr.10356-908332019-12-06T17:54:52Z Detection of stress and emotion in speech using traditional and FFT based log energy features Nwe, Tin Lay Foo, Say Wei De Silva, Liyanage C. School of Electrical and Electronic Engineering International Conference on Information, Communications and Signal Processing (4th : 2003 : Singapore) DRNTU::Engineering::Electrical and electronic engineering::Electronic systems In this paper, a novel system for detection of human stress and emotion in speech is proposed. The system makes use of FFT based linear short time Log Frequency Power Coefficients (LFPC) and TEO based nonlinear LFPC features in both time and frequency domains. The performance of the proposed system is compared with the traditional approaches which use features of LPCC and MFCC. The comparison of each approach is performed using SUSAS (Speech Under Simulated and Actual Stress)and ESMBS (Emotional Speech of Mandarin and Burmese Speakers) databases. It is observed that proposed system outperforms the traditional systems. Results show that, the system using LFPC gives the highest accuracy (87.8% for stress, 89.2% for emotion classification) followed by the system using NFD-LFPC feature. While the system using NTD-LFPC feature gives the lowest accuracy. Published version 2009-06-22T01:15:06Z 2019-12-06T17:54:52Z 2009-06-22T01:15:06Z 2019-12-06T17:54:52Z 2003 2003 Conference Paper Nwe, T . L., Foo, S. W., & De Silva, L. C.(2003). Stress and Emotion in Speech Using Traditional and FFT. In Proceedings of the 4th International Conference on Information, Communications and Signal Processing, (pp.1619-1623). Singapore: IEEE. https://hdl.handle.net/10356/90833 http://hdl.handle.net/10220/4631 en © IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. http://www.ieee.org/portal/site 5 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Electronic systems Nwe, Tin Lay Foo, Say Wei De Silva, Liyanage C. Detection of stress and emotion in speech using traditional and FFT based log energy features |
description |
In this paper, a novel system for detection of human stress and emotion in speech is proposed. The system makes use of FFT based linear short time Log Frequency Power Coefficients (LFPC) and TEO based nonlinear LFPC features in both time and frequency domains. The performance of the proposed system is compared with the traditional approaches which use features of LPCC and
MFCC. The comparison of each approach is performed using SUSAS (Speech Under Simulated and Actual Stress)and ESMBS (Emotional Speech of Mandarin and Burmese
Speakers) databases. It is observed that proposed system outperforms the traditional systems. Results show that, the system using LFPC gives the highest accuracy (87.8% for
stress, 89.2% for emotion classification) followed by the system using NFD-LFPC feature. While the system using
NTD-LFPC feature gives the lowest accuracy. |
author2 |
School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Nwe, Tin Lay Foo, Say Wei De Silva, Liyanage C. |
format |
Conference or Workshop Item |
author |
Nwe, Tin Lay Foo, Say Wei De Silva, Liyanage C. |
author_sort |
Nwe, Tin Lay |
title |
Detection of stress and emotion in speech using traditional and FFT based log energy features |
title_short |
Detection of stress and emotion in speech using traditional and FFT based log energy features |
title_full |
Detection of stress and emotion in speech using traditional and FFT based log energy features |
title_fullStr |
Detection of stress and emotion in speech using traditional and FFT based log energy features |
title_full_unstemmed |
Detection of stress and emotion in speech using traditional and FFT based log energy features |
title_sort |
detection of stress and emotion in speech using traditional and fft based log energy features |
publishDate |
2009 |
url |
https://hdl.handle.net/10356/90833 http://hdl.handle.net/10220/4631 |
_version_ |
1681034328872583168 |