Enhancement of an Arabic Speech Emotion Recognition System

摘要

In this paper, a novel two phase model is proposed to enhance an emotion recognition system. The system recognizes three emotions, happy, angry and surprised from a realistic Arabic speech corpus. Thirty five classification models were applied and the Sequential minimal optimization (SMO) classifier gave the best result with 95.52% accuracy. After applying the two- phase proposed model, an in enhancement of 3% is achieved for all classification methods. The model is then verified by two training sets and results are analyzed.