Selecting Help Messages by Using Robust Grammar Verification for Handling Out-of-Grammar Utterances in Spoken Dialogue Systems
We address the issue of out of grammar (OOG) utterances in spoken dialogue systems by generating help messages Help message generation for OOG utterances is a challenge because language under standing based on automatic speech recognition (ASR) of OOG utterances is usually erroneous important words are often misrecognized or missing from such utterances Our grammar verification method uses a weighted finite state transducer to accurately identify the grammar rule that the user Intended to use tor the utterance even if important words are missing from the ASR results We then use a ranking algorithm Rank Boost to rank help message candidates in order of likely usefulness Its features include the grammar verification results and the utterance history representing the user s experience
spoken dialogue system help generation out of grammar utterances novice user utterance history