Topic Switching Strategies for Spoken Dialogue Systems

被引:0
|
作者
Heinroth, Tobias [1 ]
Koleya, Savina [1 ]
Minker, Wolfgang [1 ]
机构
[1] Univ Ulm, Inst Informat Technol, D-89081 Ulm, Germany
关键词
spoken dialogue strategies; multitasking; HCI;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
One of the most important challenges researchers are facing within the field of Spoken Dialogue Systems is that life is neither domain dependent nor driven by a single task. In the recent past various methods to handle multiple tasks or topics in parallel within spoken human-human and human-computer dialogues have been investigated. In this paper we compare several task switching approaches such as discourse markers and task recovery methods. The aim of our study is to reveal which strategies users prefer regarding metrics such as efficiency, friendliness, and reliability. Furthermore we investigate how the different strategies influence the cognitive capacity of the subjects. The dialogues used for the study have been implemented utilising the Owl Speak Spoken Dialogue Manager, which applies ontologies as dialogue models that can be dynamically combined during runtime.
引用
收藏
页码:2088 / 2091
页数:4
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