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Task Lineages: Dialog State Tracking for Flexible Interaction

Publication
Sep 13, 2016
Abstract

We consider the gap between user demands for seamless handling of complex interactions, and recent advances in dialog state tracking technologies. We propose a new statistical approach, Task Lineage-based Dialog State Tracking (TL-DST), aimed at seamlessly orchestrating multiple tasks with complex goals across multiple domains in continuous interaction. TL-DST consists of three components: (1) task frame parsing, (2) context fetching and (3) task state update (for which TL-DST takes advantage of previous work in dialog state tracking). There is at present very little publicly available multi-task, complex goal dialog data; however, as a proof of concept, we applied TL-DST to the Dialog State Tracking Challenge (DSTC) 2 data, resulting in state-of-the-art performance. TLDST also outperforms the DSTC baseline tracker on a set of pseudo-real datasets involving multiple tasks with complex goals which were synthesized using DSTC3 data.

  • 17th Annual SIGdial Meeting on Discourse and Dialogue ([ACRONYM] SIGdial 2016)
  • Conference/Workshop Paper

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