This paper addresses the problem of out of vocabulary (OOV) utterance detection for spoken language systems in an open microphone environment. This problem is becoming crucial as use of spoken language systems grows beyond the research laboratory. In the past this problem has been addressed in the context of keyword spotting, e.g., for connected digits in a telephone environment and more recently in OOV word detection in a large vocabulary continuous speech recognition system. We develop a novel technique for designing a lexical garbage model that takes advantage of application specific knowledge and any potential bias in the recognizer. We do this through the formulation of a recognizer response function.