1. A method for emotion recognition, comprising: extracting one or more auditory attention features from an auditory spectrum for an input window of sound; generating one or more feature maps corresponding to the one or more auditory attention features; and extracting an auditory gist vector from each of the one or more feature maps; obtaining a cumulative gist vector through combination of each auditory gist vector extracted from the one or more feature maps; and determining one or more emotion classes corresponding to the input window of sound by mapping the cumulative gist vector to one or more emotion classes.
1. A method for emotion recognition, comprising: extracting one or more auditory attention features from an auditory spectrum for an input window of sound; generating one or more feature maps corresponding to the one or more auditory attention features; and extracting an auditory gist vector from each of the one or more feature maps; obtaining a cumulative gist vector through combination of each auditory gist vector extracted from the one or more feature maps; and determining one or more emotion classes corresponding to the input window of sound by mapping the cumulative gist vector to one or more emotion classes. 3. The method of claim 1 , wherein determining the auditory spectrum involves performing a Fourier Transform on the input window of sound.