Confidence measures for spontaneous speech recognition
نویسندگان
چکیده
For many practical applications of speech recognition systems, it is desirable to have an estimate of con dence 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 con dence tagger JANKA, which is able to provide con dence information for the words in 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%.
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تاریخ انتشار 1997