In this work hands-free continuous speech recognition based on microphone arrays is investigated. A set of experiments was carried out using arrays having different numbers of omnidirectional microphones as well as different configurations. Both real and simulated array signals, generated by means of the image method, were used. An enhanced input to a recognizer based on Hidden Markov Models was obtained by a time delay compensation module providing a beamformed signal. HMM adaptation was used to realign the recognizer acoustic modeling to the given acoustic condition.