In this paper we propose an entropy-optimized channel error mitigation technique with a low computational complexity and moderate memory requirements, suitable for transmissions over wireless channels. We apply it to Distributed Speech Recognition (DSR), getting an improvement of around 3% in word accuracy over the recognition performance obtained by the mitigation technique proposed in the ETSI standard for DSR (ETSIES- 201-108 v1.1.2) for bad channel conditions (GSMEP3 error pattern).