Sixth International Conference on Spoken Language Processing (ICSLP 2000)
October 16-20, 2000
DeepListener: Harnessing Expected Utility to Guide Clarification Dialog in Spoken Language Systems
Eric Horvitz, Tim Paek
Microsoft Research, Redmond, WA, USA
We describe research on endowing spoken language systems
with the ability to consider the cost of misrecognition, and using
that knowledge to guide clarification dialog about a userís
intentions. Our approach relies on coupling utility-directed
policies for dialog with the ongoing Bayesian fusion of evidence
obtained from multiple utterances recognized during an
interaction. After describing the methodology, we review the
operation of a prototype system called DeepListener.
DeepListener considers evidence gathered about utterances over
time to make decisions about the optimal dialog strategy or realworld
action to take given uncertainties about a userís intentions
and the costs and benefits of different outcomes.
Horvitz, Eric / Paek, Tim (2000):
"Deeplistener: harnessing expected utility to guide clarification dialog in spoken language systems",
In ICSLP-2000, vol.1, 226-229.