Reduction of Diffuse Noise in Mobile and Vehicular Applications

Abstract

In this chapter, we describe a hybrid subband adaptive speech enhancement system, implemented on an efficient ultra-low resource hardware platform utilizing oversampled generalized DFT filterbanks. Two analysis filterbanks decompose the two inputs (reference noise and noisy speech) into two sets of subband signals. In each subband, a subband adaptive filtering noise reduction block processes the two subband signals to reduce the noise producing a single signal which is followed by further noise reduction through Wiener filtering. Next, a synthesis filterbank converts the processed subband signals back into the time-domain. We have evaluated the performance of the hybrid noise reduction system in various real-life noise fields occurring in mobile and vehicular applications. Two closely spaced microphones make recordings in these noise fields. Signals from one microphone are used directly and represent the reference noise signal while signals from the other microphone are added to speech materials chosen from the TIMIT database before being used as the contaminated primary signal. It is demonstrated that all the noise recordings closely obey a diffuse noise field model. As the hybrid enhancement system is specifically designed to handle diffuse noise fields, it outperforms both the SAF and standard Wiener filtering in all sets of recordings. The superiority of the hybrid system is especially noted in the case of lowpass noise and intense noise conditions.