Friendly interfacing to simple speech recognizers

Abstract We describe improvements to the recognition performance of a simple commercial speech recognizer. Topics include the selection of acoustically distinct words; a method of ‘training’ (storing utterances for later use as templates) which mimics the real task, and therefore reduces the difference in diction between training and task; the representation of variability in diction by storing repeated examples of each utterance separately, instead of using a simple statistical average; and the construction of an adaptive algorithm which updates its templates at appropriate moments. The results of empirical investigations with the adaptive algorithm show a very considerable improvement in performance. We argue that the development of speech recognizers has given the hardware undue attention, and that a rigorous attack on adaptive recognition, treated as a problem in control theory, would lead to a sophisticated interface to complement sophisticated hardware. The system we describe has.been successfully u...