Conversational Semantic Parsing for Dialog State Tracking

Understand

We consider a new perspective on dialog state tracking (DST), the task of estimating a user's goal through the course of a dialog.

• By formulating DST as a semantic parsing task over hierarchical representations, we can incorporate semantic compositionality, cross-domain knowledge sharing and co-reference.
• We present TreeDST, a dataset of 27k conversations annotated with tree-structured dialog states and system acts.
• We describe an encoder-decoder framework for DST with hierarchical representations, which leads to 20% improvement over state-of-the-art DST approaches that operate on a flat meaning space of slot-value pairs.