Utterance　verification　provides　the　speech　recognition　system　a　user-friendly　interaction.　However,　small-vocabulary　system　using　DTW　algorithm　cannot　afford　HMM　based　utterance　verification.　So,　to　equip　the　DTW　based　recognizer　with　effective　utterance　verification　becomes　an　essential　problem　in　a　low　computational　application.　We　proposed　a　new　utterance　verification　method,　combining　both　statistic　and　distance　measure　capability,　to　map　DTW　distance　to　a　certain　likelihood.　The　likelihood　as　a　confidence　measure　performs　a　good　ability　of　both　speech　recognition　and　utterance　verification.　With　a　test　set　of　fifteen　words,　at　5.24%　false　rejection,　the　verification　method　brought　on　10.44%　false　alarm　rate　and　93.61　%　accuracy.　Furthermore,　94.76%　out-of-vocabulary　utterances　were　correctly　rejected.　©　2010　IEEE.