Confidence measures for spontaneous speech recognition

For many practical applications of speech recognition systems, it is desirable to have an estimate of confidence for each hypothesized word, i.e. to have an estimate of which words of the output of the speech recognizer are likely to be correct and which are not reliable. We describe the development of the measure of the confidence tagger JANKA, which is able to provide confidence information for the words at the output of the speech recognizer JANUS-3-SR. On a spontaneous German human-to-human database, JANKA achieves a tagging accuracy of 90% at a baseline word accuracy of 82%.