Speech Signal Enhancement Using a Microphone Array

This thesis describes the design and implementation of a speech enhancement system that uses microphone array beamforming and speech enhancement algorithms applied to a speech signal in a multiple source environment. The goal of the system is to improve the quality of the primary speech signal. Beamfonners work by means of steering an array of microphones towards a desired look direction through utilizing signal information rather than physically moving the array. They accomplish this through minimizing the energy of interference sources and noise in non-look directions while increasing the energy of the signal in the look direction. In this research, two beamfoming methods are examined: the delay and sum (DS) beamformer and the minimum variance distortionless response (MVDR) beamformer. The input signals are first split into frequency bands so that narrowband beamfonning techniques can be used. Multiple source Wiener filtering and multiple source spectral subtraction enhancement algorithms are incorporated into the two methods of beamforming. The algorithms utilize signal estimates of each source obtained from the initial beamfonning algorithms as inputs. These multiple source enhancement algorithms result in iterative techniques to improve those estimates while improving the signal to noise ratio of the primary source. The experimental setup presented here consists of both two and three speech sources using a linear microphone input system. The algorithms are performed on both simulated experimental setups and on data obtained from a data acquisition system in an acoustically treated sound room. To measure the improvement in quality of the enhanced signal, overall SNR and segmental SNR improvement is determined for the original, beamformed, and enhanced signal. In addition to these quality improvement metrics, listener opinion testing is performed.