In order to improve the single-mode emotion recognition rate, the bimodal fusion method based on speech
and facial expression was proposed. Here emotion recognition rate can be defined as ratio of number of images properly
recognized to the number of input images. Single mode emotion recognition term can be used either for emotion recognition
through speech or through facial expression. To increase the rate we combine these two methods by using bimodal fusion.
To do the emotion detection through facial expression we use adaptive sub layer compensation (ASLC) based facial edge
detection method and for emotion detection through speech we use well known SVM. Then bimodal emotion detection is
obtained by using probability analysis.