Nicholas Kushmerick, Tessa Lau
IUI 2005
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. Based on rules learned from a set of training dialogues, adaptive TOOT constructs a user model representing whether the user is having speech recognition problems as a particular dialogue progresses. Adaptive TOOT then automatically adapts its dialogue strategies based on this dynamically changing user model. An empirical evaluation of the system demonstrates the utility of the approach.
Nicholas Kushmerick, Tessa Lau
IUI 2005
Atsuyoshi Nakamura, Naoki Abe
Electronic Commerce Research
Christine Robson, Sean Kandel, et al.
CHI 2011
Charles Wieeha, Pedro Szekely
CHI EA 2001