Emotion Detection through Speech and Facial Expressions

Kudiri, K.M. and Said, A.M. and Nayan, M.Y. (2015) Emotion Detection through Speech and Facial Expressions. In: UNSPECIFIED.

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Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

Human machine interaction is one of the most burgeoning area of research in the field of information technology. To date a majority of research in this field has been conducted using unimodal and multimodal systems with asynchronous data. Because of the above, the improper synchronization, which has become a common problem, due to that, the system complexity increases and the system response time decreases. To counter this problem, a novel approach has been introduced to predict human emotions using human speech and facial expressions. The approach uses two feature vectors, namely, relative bin frequency coefficient (RBFC) and relative sub-image based coefficient (RSB) for speech and visual data respectively. Support vector machine with radial basis kernel is used for feature level classification based fusion technique between two modalities. The proposed novel approach has resulted in galvanizing results for a myriad of inputs and can be adapted to asynchronous data. © 2014 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Impact Factor: cited By 4
Uncontrolled Keywords: Bins; Face recognition; Support vector machines, Emotion detection; Facial Expressions; Frequency coefficient; Fusion techniques; Human machine interaction; Multimodal system; Subimages; System response time, Human computer interaction
Depositing User: Ms Sharifah Fahimah Saiyed Yeop
Date Deposited: 26 Mar 2022 03:23
Last Modified: 26 Mar 2022 03:23
URI: http://scholars.utp.edu.my/id/eprint/31588

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