Flexible Mixed-Initiative Dialogue Management using Concept-Level Con dence Measures of Speech Recognizer Output

We present a method to realize exible mixedinitiative dialogue, in which the system can make e ective con rmation and guidance using concept-level con dence measures (CMs) derived from speech recognizer output in order to handle speech recognition errors. We de ne two concept-level CMs, which are on contentwords and on semantic-attributes, using 10-best outputs of the speech recognizer and parsing with phrase-level grammars. Content-word CM is useful for selecting plausible interpretations. Less con dent interpretations are given to conrmation process. The strategy improved the interpretation accuracy by 11.5%. Moreover, the semantic-attribute CM is used to estimate user's intention and generates system-initiative guidances even when successful interpretation is not obtained.