TY - GEN
T1 - Sayisal ses sinyallerinden duygu algilama
AU - Yaslan, Samet
AU - Günsel, Bilge
PY - 2005
Y1 - 2005
N2 - This paper presents a system for emotion recognition from audio. The emotion recognition problem is described as a four class classification problem in a 17 dimensional feture space. Currently, considered emotions are: Anger, happiness, sadness and unemotional. A SVM classifier with Gaussian RBF kernel is used for the classification. Experimental results obtained on a database that contains 11 different sentences recorded by 11 different speakers in four different emotions, are reported. It is shown that the developed system enables classifying four emotions with higher than 70% accuracy, with a false alarm ratio is less than 30%.
AB - This paper presents a system for emotion recognition from audio. The emotion recognition problem is described as a four class classification problem in a 17 dimensional feture space. Currently, considered emotions are: Anger, happiness, sadness and unemotional. A SVM classifier with Gaussian RBF kernel is used for the classification. Experimental results obtained on a database that contains 11 different sentences recorded by 11 different speakers in four different emotions, are reported. It is shown that the developed system enables classifying four emotions with higher than 70% accuracy, with a false alarm ratio is less than 30%.
UR - https://www.scopus.com/pages/publications/33846615550
U2 - 10.1109/SIU.2005.1567770
DO - 10.1109/SIU.2005.1567770
M3 - Konferans katkısı
AN - SCOPUS:33846615550
SN - 0780392396
SN - 9780780392397
T3 - Proceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005
SP - 656
EP - 659
BT - Proceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005
T2 - IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005
Y2 - 16 May 2005 through 18 May 2005
ER -