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Recent paper on evaluation of spoken dialogue systems indicates that better algorithms are needed for the presentation of complex information in speech. Current dialogue systems often rely on presenting sets of options and their attributes sequentially. This place a large memory burden on users, who have to remember complex trade-offs between multiple options and their attributes. To address these problems they build on previous paper using multiattribute decision theory to devise speech-planning algorithms that present usertailored summaries, comparisons and recommendations that allow users to focus on critical differences between options and their attributes. They discuss the differences between speech and text planning that result from the particular demands of the speech situation.
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