This work emphasizes on recognizing different emotions from speech signals using new technologies of the Neural Networks. Historical background and other technical information are illustrated in details. Using five different ANN architectures, a large online database with extracted features from different speeches, it will be shown that different factors have high impact on the classification success rate. Several experiments were carried out to show how these factors can be tuned to achieve a success rate of 85% and even more. Results and data are all submitted with a declaring steps to help new workers to start.

NERMINE A. HENDY AlexandriaEgyptEducation2013 M.Sc in Communication Engineering, Electrical Engineering Department, Faculty of Engineering, Alexandria UniversityPublicationsNermine Ahmed Hendy, Hania Farag Ph.D., "Emotion Recognition Using Neural Network: A Comparative Study," in ICSPPRA 2013