Using Adaboost Algorithm along with Artificial neural networks for efficient human emotion recognition from speech

Emotion Recognition from speech has evolved itself as the most significant research area in the field of affective computing. In this paper, two emotional speech datasets, have been analyzed, based on gender distinction (male and female speech). This paper introduces a new approach of speech-emotion recognition based on the use of AdaBoost classification Algorithm. Artificial neural network has been implemented for pattern classification and recognition. English is used as the basic language for the testing of the method. We have recognized the emotions into four different groups happy, normal, sad and anger by using AdaBoost Algorithm and ANN. The output for the two datasets are evaluated and analyzed.