Exploiting inter-microphone agreement for hypothesis combination in distant speech recognition

A multi-microphone hypothesis combination approach, suitable for the distant-talking scenario, is presented in this paper. The method is based on the inter-microphone agreement of information, extracted at speech recognition level. Particularly, temporal information is exploited to organize the clusters that shape the resulting confusion network, and to reduce the global hypothesis search space. As a result, a single combined confusion network is generated from multiple lattices. The approach offers a novel perspective to solutions based on confusion network combination. The method was evaluated in a simulated domestic environment equipped with largely spaced microphones. The experimental evidence suggests that results, comparable or, in some cases, better than the state of the art, can be achieved under optimal configurations with the proposed method.