A new approach of audio emotion recognition

Chien Shing Ooi, Kah Phooi Seng, Li-Minn Ang, Li Wern Chew

Research output: Contribution to journalArticlepeer-review

55 Citations (Scopus)
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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.
Original languageEnglish
Pages (from-to)5858-5869
Number of pages11
JournalExpert Systems with Applications
Volume41
Issue number13
Early online dateMar 2014
DOIs
Publication statusPublished - 01 Oct 2014

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