Technical Program

Paper Detail

Paper:MMSA-P2.1
Session:Intelligent Processing Techniques for Multimedia Systems and Applications
Time:Monday, May 24, 09:30 - 11:00
Presentation: Poster
Topic: Multimedia Systems and Applications: Multimedia Understanding and Recognition
Title: A NEURAL NETWORK APPROACH FOR HUMAN EMOTION RECOGNITION IN SPEECH
Authors: Muhammad Waqas Bhatti; University of Sydney 
 Yongjin Wang; Ryerson University 
 Ling Guan; Ryerson University 
Abstract: In this paper, we present a language-independent emotion recognition system for the identification of human affective state in the speech signal. A corpus of emotional speech from various subjects, speaking different languages is collected for developing and testing the feasibility of the system. The potential prosodic features are first identified and extracted from the speech data. Then we introduce a systematic feature selection approach which involves the application of Sequential Forward Selection (SFS) with a General Regression Neural Network (GRNN) in conjunction with a consistency-based selection method. The selected features are employed as the input to a Modular Neural Network (MNN) to realize the classification of emotions. The proposed system gives quite satisfactory emotion detection performance, yet demonstrates a significant increase in versatility through its propensity for language independence.
 
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