Abstract This paper presents a HMM Local Optimal state Path-based Data Imputation (LOPDI) algorithm. Speech feature vector sequences are presumed to be the outputs of an L state HMM. The HMM state sequence is estimated by local optimal path procedure. Then, "missing" data is recovered by MAP procedure. Experimental result shows that LOPDI algorithm can greatly increase automatic speech recognition system’s robustness against additive noise.