Speech emotion recognition system based on genetic algorithm and neural network

This paper describes a new speech emotion recognition system aimed at improving the speech emotion recognition rate. Seven discrete emotional states (anger, disgust, fear, joy, neutral, sadness, and surprise) are classified throughout the work. The system is comprised of three main sections, a pre-processing section, a feature extracting section and a neural network processing section. Genetic algorithm (GA) was first used to replace Steepest Descent Method (SDM) and make a global search of optimal weight in neural network. Results are given on speaker dependent case using the Chinese corpus of emotional speech synthesis database. Recognition experiments show that the method is effective and high speed for emotion recognition.

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