EUROSPEECH 2001 Scandinavia
Some stochastic models like Markov decision process (MDP) are used to model the dialogue manager. MDP-based system degrades fast when uncertainty about userí6s intention increases. We propose a novel dialogue model based on the partially observable Markov decision process (POMDP). We use hidden system states and user intentions as the state set, parser results and low-level information as the observation set, domain actions and dialogue repair actions as the action set. Here the low-level information is extracted from different input modals using Bayesian networks. Because of the limitation of exact algorithms, we focus on heuristic methods and their applicability in dialogue management.
Bibliographic reference. Zhang, Bo / Cai, Qingsheng / Mao, Jianfeng / Chang, Eric / Guo, Baining (2001): "Spoken dialogue management as planning and acting under uncertainty", In EUROSPEECH-2001, 2169-2172.