Hearing impaired persons suffer from speech degradation in noisy environments. They rely on hearing aids that cannot only reduce the noise but also improve the intelligibility of the received signal. Until recently, only bilateral speech enhancement techniques were developed for hearing aids, i.e., the signals were processed independently for each ear and thereby the binaural human auditory system could not be matched. Bilateral configurations may distort crucial binaural information as needed to localize sound sources correctly and to improve speech perception in noise. The availability of wireless technologies leads from monaural or bilateral hearing aids to binaural processing strategies. Thus, new digital signal processing strategies can be realized for speech enhancement in hearing aids.
A well-known method for speech enhancement using a single microphone is the Wiener filter. But there are also many other MMSE (minimum mean square error), MAP (maximum a posteriori), and ML (maximum likelihood) estimators derived from Bayesian estimation theory that can be used for speech enhancement.
In this thesis, the applicability of different speech enhancement techniques for binaural hearing aids shall be investigated. Therefore, the different methods need to be compared with respect to noise reduction, speech distortion, and spectral distortion for speech being corrupted by nonstationary noise. A theoretical as well as an experimental investigation by Matlab simulations is necessary. Well-documented and well-structured software is important. The thesis can be written in German or English.
Matlab, Digital Signal Processing course, interest in audio