Performance analysis of Speech enhancement methods in Hands-free Communication with emphasis on Wiener Beamformer

Abstract: The main objective of this thesis, which is a collaborative work between a group of four, is to remove the unwanted components i.e. background noise present in speech signal which affects in the hands-free speech communication. The background noise i.e. noise and echo are removed using different methods in Hands-free speech communication for enhancement of acoustic speech signal. The Noise is suppressed using adaptive beam formers like Wiener Beam former, Elko‟s Beam former, Maximum SNIR Beamformer and Delay and Sum beam former as they have the ability to enhance the desired speech signals while suppressing the noise sources assumed from other directions. The behavior of these beam formers is tested under different noise environments. Echo Cancellation is achieved by implementing adaptive noise feedback cancellation system using NLMS algorithm under reverberant conditions. This paper mainly concentrates on the offline MATLAB implementation of Wiener Beamformer and performance is evaluated by considering the different objective measures in different noisy environments. Speech signals from the uncontrolled environments contain degradation components i.e. background noise, interference, acoustic feedback along with the required speech components. These degraded components are superimposed with the desired speech which is a severe problem in hands-free speech communication for example in hearing impaired persons. Hence, they suffer from reduced speech intelligibility and quality which make their communication troublesome. Therefore, speech enhancement is necessary in hands-free speech communication devices for degraded speech. Wiener Beam former is implemented and simulated in MATLAB under different noise environments in order to increase the speech intelligibility and quality. The performance of the Wiener Beamformer is evaluated by considering the objective measure parameters such SNR, SD and PESQ under different noisy environments. These parameters are measured by assuming input SNR levels at 0dB, 5dB, 10 dB, 15 dB, 20 dB and 25 dB. The increased use of hands free communication systems such as computer communications, video conferencing and vehicle mounted mobile phones demands the acoustic echo cancellation. The echo i.e. uncontrolled acoustic feedback is cancelled using NLMS algorithm which forms an adaptive feedback noise cancellation system. The amount echo cancellation is measured by ERLE parameter.