1. A method for tone/intonation recognition in spoken language processing, comprising: a) determining an auditory spectrum for an input window of sound; b) extracting one or more multi-scale features from the auditory spectrum, wherein each multi-scale feature is extracted using a separate two-dimensional spectro-temporal receptive filter; c) generating one or more feature maps corresponding to the one or more multi-scale features; d) extracting an auditory gist vector from each of the one or more feature maps; e) obtaining a cumulative gist vector through augmentation of each auditory gist vector extracted from the one or more feature maps; and f) determining one or more tonal characteristics corresponding to the input window of sound by mapping the cumulative gist vector to one or more tonal characteristics using a machine learning algorithm.