Acoustic Noise Suppression for Speech Signals using Auditory Masking Effects

The process of suppressing acoustic noise in audio signals, and speech signals in particular, can be improved by exploiting the masking properties of the human hearing system. These masking properties, where strong sounds make weaker sounds inaudible, are calculated using auditory models. This thesis examines both traditional noise suppression algorithms and ones that incorporate an auditory model to achieve better performance. The different auditory models used by these algorithms are examined. A novel approach, based on a method to remove a specific type of noise from audio signals, is presented using a standardized auditory model. The proposed method is evaluated with respect to other noise suppression methods in the problem of speech enhancement. It is shown that this method performs well in suppressing noise in telephone-bandwidth speech, even at low Signal-to-Noise Ratios.