Automatic detection of new words in a large vocabulary continuous speech recognition system

Abstract
A preliminary investigation of techniques that automatically detect when a speaker has used a word that is not in the vocabulary of a continuous-speech recognition system is described. A technique that uses a general model for the acoustics of any word to recognize the existence of new words is developed. Using this general word model, the correct detection of new words versus the false alarm rate is measured. Experiments were run using the DARPA 1000-word Resource Management Database indicate a detection rate for new words of 74% with a false alarm rate of 3.4%.<>

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