A microphone array along with a beamformer can improve the suppression of background noise and reverb compared to a single unidirectional microphone. The focus in this thesis is on beamforming algorithms based on differential microphone arrays that are able to suppress interfering signals from different directions without affecting the desired signal from a known target direction. The array geometries and the algorithms are chosen with the aim to integrate them in a compact device and use them as a front-end for a speech recognition system. The operating principle, the design and basic characteristics of first- and second-order differential microphone arrays are presented and the selected beamforming algorithms are described. The algorithms are implemented in MATLAB. Recordings with two different microphone types are made: electret condenser microphone capsules and MEMS-microphones. The algorithms are analyzed by measuring beam patterns and their performance under real conditions. For the latter, speech recordings in a reverberant office environment with different scenarios for interfering sources are made. The evaluation of the performance is done by objective measures and by means of the word accuracy rate of a speech recognition system.