Speech Emotion Recognition Using Spectral Entropy
ICIRA '08 Proceedings of the First International Conference on Intelligent Robotics and Applications: Part II
Speech emotional features extraction based on electroglottograph
Neural Computation
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In this paper, combined features of global and time-sequence were used as the characteristic parameters for speech emotional recognition. A new method based on formula of MMD (Modified Mahalanobis Distance) was proposed to decrease the estimated errors and simplify the calculation. Four emotions including happiness, anger, surprise and sadness are considered in the paper. 1000 recognizing sentences collected from 10 speakers were used to demonstrate the effectiveness of the new method. The average emotion recognition rate reached at 95%. Comparison with method of MQDF [1] (Modified quadratic discriminant function), Data analysis also displayed that the MMD is better than MQDF.