We present a method to generate effective confirmation and guidance using concept-level confidence meausres (CM) derived from speech recognizer output in order to handle speech recognition errors. We define two concept-level CM, which are on content-words and on semantic-attributes, using 10-best outputs of the speech recognizer and parsing with phrase-level grammars. Content-words CM is useful for selecting plausible interpretations. Less confident interpretations are given to confirmation process, and non-confident ones are rejected. The strategy improved the interpretation accuracy by 11.5
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