Models & Optimisation and Mathematical Analysis Journal
Volume 6, Numéro 1, Pages 15-18
Authors : Horkous Houari .
Abstract—This work consists on the automatic recognition of the emotions in the speech, because it plays a very significant role in the communication. The automatic recognition of the emotions potentially had a broad application in the Human Machine Interaction.In this work we use prosodic (pitch, intensity and duration) and cepstral parameters MFCCs (Mel-Frequency Cepstral Coefficients) to analyze the emotions of joy and sadness. These parameters will be used in the automatic recognition of the emotions. The system of recognition is based on the method of classification GMM (Gaussian Mixture Model). The obtained results lead us to observe that the use of the prosodic and MFCCs parameters gives a very acceptable rate of recognition (82.81%).
Speech emotion, joy, sadness, prosodic, MFCC, GMM