Lateral inhibition mechanism in computational auditory model and its application in robust speech recognition

In the auditory neural system, the lateral inhibition mechanism is very common, such as in the cochlear nucleus, auditory cortex, etc. The function of this lateral inhibition is to sharpen the contrast of the temporal and spatial structures, thus prominent features of stimulation in spatial and temporal domains can be enhanced. In this paper, a new mathematical model based on lateral inhibition is proposed. Traditional feature MFCC (Mel Frequency Cepstral Coefficient) and auditory feature AFCC (Auditory Frequency Cepstral Coefficient) are processed by this model, new features can be obtained such as MFCCI and AFCCI. Experiments with the new features with a HMM show that they can improve the robustness of the recognition rate in noisy conditions