Journal article
A new approach of audio emotion recognition
Expert Systems with Applications, Vol.41(13), pp.5858-5869
2014
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.
Details
- Title
- A new approach of audio emotion recognition
- Authors
- Chien Shing Ooi (Author) - Sunway UniversityKah Phooi Seng (Author) - Edith Cowan UniversityLi-Minn Ang (Author) - Edith Cowan UniversityLi Wern Chew (Author) - Intel Microelectronics (M) Sdn Bdh - Palau Pinang, Malaysia
- Publication details
- Expert Systems with Applications, Vol.41(13), pp.5858-5869
- Publisher
- Elsevier Ltd
- Date published
- 2014
- DOI
- 10.1016/j.eswa.2014.03.026
- ISSN
- 0957-4174; 1873-6793; 0957-4174
- Organisation Unit
- University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Engage Research Lab
- Language
- English
- Record Identifier
- 99513788702621
- Output Type
- Journal article
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- Collaboration types
- Industry collaboration
- Domestic collaboration
- International collaboration
- Web Of Science research areas
- Computer Science, Artificial Intelligence
- Engineering, Electrical & Electronic
- Operations Research & Management Science