Finally, there is a need for systems that can learn over time as a result of their
interactions with users and adapt their behavior to both the user and the situation.
While much progress has been made in machine learning–based dialogue manage-
ment, the applications using it have generally involved fairly simple form filling where
the parameters to be learned are simple. Major challenges are to be expected when
learning is extended to the more open-ended environments of ambient intelligence.
9.6 CONCLUSIONS
This chapter described the main characteristics of spoken dialogue applications and
explored how spoken dialogue technology can be applied to the more open-ended
environments of ambient intelligence. Spoken dialogue technology is a multidisci-
plinary fi eld that has attracted considerable attention over recent years. It is likely
that many of the challenges and issues raised in this chapter will be the subject of
future research, resulting in advances in the underlying technologies and providing
support for a wide range of users, including senior citizens and peo ple with dis-
abilities as well as, more generally, users who require assistance in managing their
everyday activities.
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