Dialog repair based on discrepancies between user model predictions and speech recognition results
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United States of America Patent
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-
Aug 14, 2012
Grant Date -
Oct 4, 2007
app pub date -
Mar 30, 2006
filing date -
Mar 30, 2006
priority date (Note) -
In Force
status (Latency Note)
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Abstract
An architecture is presented that leverages discrepancies between user model predictions and speech recognition results by identifying discrepancies between the predictive data and the speech recognition data and repairing the data based in part on the discrepancy. User model predictions predict what goal or action speech application users are likely to pursue based in part on past user behavior. Speech recognition results indicate what goal speech application users are likely to have spoken based in part on words spoken under specific constraints. Discrepancies between the predictive data and the speech recognition data are identified and a dialog repair is engaged for repairing these discrepancies. By engaging in repairs when there is a discrepancy between the predictive results and the speech recognition results, and utilizing feedback obtained via interaction with a user, the architecture can learn about the reliability of both user model predictions and speech recognition results for future processing.
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