Hands-free continuous speech recognition in noise using a speaker beam-former based on spectrum-entropy

Detection of the speaker position is a crucial task in hands-free speech recognition applications. In this paper we present a novel speech beam-former for noisy environments. Initially, the localization algorithm extracts a set of candidate directions of the signal sources using array signal processing methods in the frequency domain. Then, a minimum variance (MV) beam-former identifies the speech signal in the direction where the signal´s spectrum entropy is minimized. The proposed method is evaluated by a phoneme recognition system using noise recordings from an air-condition fan and the TIMIT speech corpus. Extended experiments, carried out in the range of 25–0 dB, show almost perfect estimation of the speaker DOA in all cases. As a consequence, the recognition rate increases significantly compared to the rate obtained by a single microphone. The recognition improvement increases especially in very low SNRs.