SIGdial 2016

17th Annual SIGdial Meeting on Discourse and Dialogue

Reference Resolution in Situated Dialogue with Learned Semantics

Xiaolong Li and Kristy Boyer
Understanding situated dialogue requires identifying referents in the environment to which the dialogue participants refer. This reference resolution problem, often in a complex environment with high ambiguity, is very challenging. We propose an approach that addresses those challenges by combining learned semantic structure of referring expressions with dialogue history into a ranking-based model. We evaluate the new technique on a corpus of human-human tutorial dialogues for computer programming. The experimental results show a substantial performance improvement over two recent state-of-the-art approaches. The proposed work makes a stride toward automated dialogue in complex problem-solving environments.