DSTC2
Related Papers
Dialog state tracking, a machine reading approach using Memory Network
AbstractIn an end-to-end dialog system, the aim of dialog state tracking is to accurately estimate a compact representation of the current dialog status from a sequence of noisy observations produced …...
Graph Convolutional Network with Sequential Attention for Goal-Oriented Dialogue Systems
AbstractDomain-specific goal-oriented dialogue systems typically require modeling three types of inputs, namely, (i) the knowledge-base associated with the domain, (ii) the history of the conversation, which is a sequence of …...
Self-Attentional Models Application in Task-Oriented Dialogue Generation Systems
AbstractSelf-attentional models are a new paradigm for sequence modelling tasks which differ from common sequence modelling methods, such as recurrence-based and convolution-based sequence learning, in the way that their architecture …...
Effective Sequence-to-Sequence Dialogue State Tracking
AbstractSequence-to-sequence models have been applied to a wide variety of NLP tasks, but how to properly use them for dialogue state tracking has not been systematically investigated. In this paper, …...
Beyond the Granularity: Multi-Perspective Dialogue Collaborative Selection for Dialogue State Tracking
AbstractIn dialogue state tracking, dialogue history is a crucial material, and its utilization varies between different models. However, no matter how the dialogue history is used, each existing model uses …...