In the context of the ESPRIT MASK project we face the problem of adapting a "state-of-the-art" laboratory speech recognizer for use in the real world with naive users. The speech recognizer is a software-only system that runs in real-time on a standard Risc processor. All aspects of the speech recognizer have been reconsidered from signal capture to adaptive acoustic models and language models. The resulting system includes such features as microphone selection, response cancellation, noise compensation, query rejection capability and decoding strategies for real-time recognition.