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Publication Type : Conference Paper
Source : 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), IEEE, Udupi, India (2017)
Url : https://ieeexplore.ieee.org/document/8125934
Campus : Bengaluru
School : School of Engineering
Center : Electronics Communication and Instrumentation Forum (ECIF)
Department : Electronics and Communication
Year : 2017
Abstract : The paper deals with affective computing to improve the performance of Human-Machine interaction. The focus of this work is to detect affective state of a human using speech processing techniques primarily intended for call centre applications. Limited work is reported till date on affect detection using phase derived features. A unique combination of Group delay (GD), Phase delay (PD), One Sided Autocorrelation Linear Predictive Coefficients (OSALPC) and Residual Phase (RP) are used in this work. A comparative analysis is performed using Neural Networks, Support Vector Machine (SVM) and K Nearest Neighbor (KNN) to detect seven affective states. The proposed algorithm outperforms the earlier reported work using phase derived features work by a factor of around 10% for affect detection.
Cite this Research Publication : R. K. Gowda, Nimbalker, V., Lavanya, R., Lalitha, S., and Tripathi, S., “Affective computing using speech processing for call centre applications”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017.