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NAACL
2010

Learning about Voice Search for Spoken Dialogue Systems

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Learning about Voice Search for Spoken Dialogue Systems
In a Wizard-of-Oz experiment with multiple wizard subjects, each wizard viewed automated speech recognition (ASR) results for utterances whose interpretation is critical to task success: requests for books by title from a library database. To avoid non-understandings, the wizard directly queried the application database with the ASR hypothesis (voice search). To learn how to avoid misunderstandings, we investigated how wizards dealt with uncertainty in voice search results. Wizards were quite successful at selecting the correct title from query results that included a match. The most successful wizard could also tell when the query results did not contain the requested title. Our learned models of the best wizard's behavior combine features available to wizards with some that are not, such as recognition confidence and acoustic model scores.
Rebecca J. Passonneau, Susan L. Epstein, Tiziana L
Added 14 Feb 2011
Updated 14 Feb 2011
Type Journal
Year 2010
Where NAACL
Authors Rebecca J. Passonneau, Susan L. Epstein, Tiziana Ligorio, Joshua B. Gordon, Pravin Bhutada
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