Optimizing Generative Dialog State Tracker via Cascading Gradient Descent

Byung-Jun Lee, Woosang Lim, Daejoong Kim, Kee-Eung Kim
2014 Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)  
For robust spoken dialog management, various dialog state tracking methods have been proposed. Although discriminative models are gaining popularity due to their superior performance, generative models based on the Partially Observable Markov Decision Process model still remain attractive since they provide an integrated framework for dialog state tracking and dialog policy optimization. Although a straightforward way to fit a generative model is to independently train the component probability
more » ... mponent probability models, we present a gradient descent algorithm that simultaneously train all the component models. We show that the resulting tracker performs competitively with other top-performing trackers that participated in DSTC2.
doi:10.3115/v1/w14-4338 dblp:conf/sigdial/LeeLKK14 fatcat:yj67ooxlsje2xdcmtflanmun5a