Distributed Speech Recognition involves the development of techniques to conceal the degradations that the transmission channel introduces in the speech features. This work proposes a lowcomplexity high-accuracy error concealment technique compatible with the DSR ETSI standards. This is achieved by combining three different techniques: fast MMSE estimation, Viterbi decoding with soft-data and subvector-based error detection. We also propose a method to extend this Viterbi decoding to dynamic features. The experimental results show the effectiveness of our proposal.