Predicting and Adapting to Poor Speech Recognition in a Spoken Dialogue System
نویسندگان
چکیده
Spoken dialogue system performance can vary widely for different users, as well for the same user during different dialogues. This paper presents the design and evaluation of an adaptive version of TOOT, a spoken dialogue system for retrieving online train schedules. Adaptive TOOT predicts whether a user is having speech recognition problems as a particular dialogue progresses, and automatically adapts its dialogue strategies based on its predictions. An empirical evaluation of the system demonstrates the utility of the approach.
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