Abstract In a noisy environment speech recognizers make mistakes. In order that these errors can be detected the system can synthesize the word recognized and the user can respond by saying “correction” when the word was not recognized correctly. The mistake can then be corrected. Two error-correcting strategies have been investigated. In one, repetition-with-elimination, when a mistake has been detected the system eliminates its last response from the active vocabulary and then the user repeats the word that has been misrecognized. In the other, elimination-without-repetition, the system suggests the next-most-likely word based on the output of its pattern-matching algorithm. It was found that the former strategy, with the user repeating the word, required less trials to correct the recognition errors. A model which relates the average number of corrections to the recognition rate has been developed which provides a good fit to the data.
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