Recurrent Neural Networks for Dialog State Tracking

The recent Dialog State Tracking Challenges have brought into focus the problem of accurately estimating the dialog state throughout a sequence of spoken interactions with a dialog system. Recurrent Neural Networks (RNNs) can be effectively applied to this problem, giving results which perform competitively in the shared challenge tasks. The proposed model is unique in that it eliminates the need for a spoken language understanding component, and the inherent bottleneck, by mapping directly from words to th