Affect Recognition in Human Emotional Speech using Probabilistic Support Vector Machines

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Published: Dec 31, 2022
DOI: https://doi.org/10.17762/ijritcc.v10i2s.5924
Keywords:
Human Emotional Speech, Vector Machines, human-computer interaction (HCI)

Main Article Content

Ratna Kanth Nelapati
Department of CSE, Koneru Lakshmaiah Education Foundation, Green Fields, Vaddeswaram, Guntur, Andhra Pradesh, India
Saraswathi Selvarajan
Department of Information Technology, Puducherry Technological University, Puducherry, India

Abstract

The problem of inferring human emotional state automatically from speech has become one of the central problems in Man Machine Interaction (MMI). Though Support Vector Machines (SVMs) were used in several worksfor emotion recognition from speech, the potential of using probabilistic SVMs for this task is not explored. The emphasis of the current work is on how to use probabilistic SVMs for the efficient recognition of emotions from speech. Emotional speech corpuses for two Dravidian languages- Telugu & Tamil- were constructed for assessing the recognition accuracy of Probabilistic SVMs. Recognition accuracy of the proposed model is analyzed using both Telugu and Tamil emotional speech corpuses and compared with three of the existing works. Experimental results indicated that the proposed model is significantly better compared with the existing methods.

Article Details

How to Cite
Nelapati, R. K. ., & Selvarajan, S. . (2022). Affect Recognition in Human Emotional Speech using Probabilistic Support Vector Machines. International Journal on Recent and Innovation Trends in Computing and Communication, 10(2s), 166–173. https://doi.org/10.17762/ijritcc.v10i2s.5924
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Vol. 10 No. 2s (2022): Computer Science Applications: Innovation and Trends
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Articles

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