Paper: Learning about Voice Search for Spoken Dialogue Systems

ACL ID N10-1126
Title Learning about Voice Search for Spoken Dialogue Systems
Venue Human Language Technologies
Session Main Conference
Year 2010

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 data- base. To avoid non-understandings, the wizard directly queried the application database with the ASR hypothesis (voice search). To learn how to avoid misunderstandings, we investi- gated how wizards dealt with uncertainty in voice search results. Wizards were quite suc- cessful at selecting the correct title from query results that included a match. The most suc- cessful 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 ...