Smartphone-Based Single and Dual Microphone Speech Enhancement Algorithms for Hearing Study
Speech Enhancement (SE) is elemental in many real world applications. In the last two decades, extensive studies have been carried out on single and multi-channel SE techniques. In this thesis, three novel SE algorithms have been proposed that can be used for Hearing Aid Devices using a smartphone as their assistive device. The first SE method exploits the information of formant locations to improve the speech quality and intelligibility of the Super-Gaussian Joint Maximum aposterori (SGJMAP) SE method. The second method is the extension of this work on the Log Spectral Minimum Mean Square Error Amplitude Estimator (Log-MMSE) which is a well-known SE algorithm. The third method is a real time Blind Source Separation (BSS) method based on Independent Vector Analysis (IVA) for convolutive mixtures. Objective and subjective evaluation of the developed techniques show substantial improvements in speech quality and intelligibility.