Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/43153
Title: Classification of stress in speech using linear and nonlinear features
Authors: Nwe, T.L. 
Foo, S.W.
De Silva, L.C. 
Issue Date: 2003
Source: Nwe, T.L.,Foo, S.W.,De Silva, L.C. (2003). Classification of stress in speech using linear and nonlinear features. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings 2 : 9-12. ScholarBank@NUS Repository.
Abstract: In this paper, three systems for classification of stress in speech are proposed. The first system makes use of linear short time Log Frequency Power Coefficients (LFPC), the second employs Teager Energy Operator (TEO) based Nonlinear Frequency Domain LFPC features (NFD-LFPC) and the third uses TEO based Nonlinear Time Domain LFPC features (NTD-LFPC). The systems were tested using SUSAS (Speech Under Simulated and Actual Stress) database to categorize five stress conditions individually. Results show that, the system using LFPC gives the highest accuracy, followed by the system using NFD-LFPC features. While the system using NTD-LFPC features gives the worst performance. For the system using linear LFPC features, the average accuracy of 84% and the best accuracy of 95% were obtained in classifying five stress categories.
Source Title: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/43153
ISSN: 15206149
Appears in Collections:Staff Publications

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