A new approach of audio emotion recognition
Abstract
A new architecture of intelligent audio emotion recognition is proposed in this paper. It fully utilizes both prosodic and spectral features in its design. It has two main paths in parallel and can recognize 6 emotions. Path 1 is designed based on intensive analysis of different prosodic features. Significant prosodic features are identified to differentiate emotions. Path 2 is designed based on research analysis on spectral features. Extraction of Mel-Frequency Cepstral Coefficient (MFCC) feature is then followed by Bi-directional Principle Component Analysis (BDPCA), Linear Discriminant Analysis (LDA) and Radial Basis Function (RBF) neural classification. This path has 3 parallel BDPCA + LDA + RBF sub-paths structure and each handles two emotions. Fusion modules are also proposed for weights assignment and decision making. The performance of the proposed architecture is evaluated on eNTERFACE'05 and RML databases. Simulation results and comparison have revealed good performance of the proposed recognizer.
Document Type
Journal Article
Date of Publication
1-1-2014
Faculty
Faculty of Health, Engineering and Science
School
School of Engineering
Copyright
subscription content
Publisher
Elsevier
Comments
Ooi C.S., Seng K.P., Ang L.-M., Chew L.W. (2014). A new approach of audio emotion recognition. Expert Systems with Applications, 41(13), 5858-5869. Available here