IIUM Repository

Valence-arousal approach for speech emotion recognition system

Kamaruddin, Norhaslinda and Abdul Rahman, Abdul Wahab (2013) Valence-arousal approach for speech emotion recognition system. In: 2013 International Conference on Electronics, Computer and Computation (ICECCO 2013), 7-8 Nov. 2013, Ankara, Turkey.

[img] PDF - Published Version
Restricted to Repository staff only

Download (402kB) | Request a copy

Abstract

The current state-of-the-art speech emotion recognition approaches focus on discrete emotion classification to suit the users’ need. However, in more practical perspective,emotion is deemed complex to be individually segregated and it is a continuous process that will change dynamically over time. Subsequently, no researcher can really claim of being able to find the threshold discriminating one emotion to another. In this paper, an alternative approach of Valence-Arousal is introduced based on the psychologists’ understanding that emotion can be represented in two emotion primitives of Valence and Arousal. Empirical results show potential of the proposed approach, which achieved reasonable accuracy with better speech emotion understanding and analysis.

Item Type: Conference or Workshop Item (Full Paper)
Additional Information: 6145/38077 (ISBN: 978-1-4799-3343-3, DOI: 10.1109/ICECCO.2013.6718259)
Uncontrolled Keywords: Speech emotion recognition, affective space model, Mel Frequency Cepstral Coefficient, neural network, fuzzy neural network
Subjects: T Technology > T Technology (General) > T55.4 Industrial engineering.Management engineering. > T57 Applied mathematics. Quantitative methods. Operation research. System analysis
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Information and Communication Technology
Kulliyyah of Information and Communication Technology
Depositing User: Ahmad Nazreen Mohd Shamsuri (PT)
Date Deposited: 10 Sep 2014 14:29
Last Modified: 04 Apr 2016 15:12
URI: http://irep.iium.edu.my/id/eprint/38077

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year