89 citations · 110 across the 16 of their papers we have counts for
5 papers · 1 filter
The BURCHAK corpus: a Challenge Data Set for Interactive Learning of Visually Grounded Word Meanings
Yanchao Yu, Arash Eshghi, Gregory Mills +1
We motivate and describe a new freely available human-human dialogue dataset for interactive learning of visually grounded word meanings through ostensive definition by a tutor to…
Training an adaptive dialogue policy for interactive learning of visually grounded word meanings
Yanchao Yu, Arash Eshghi, Oliver Lemon
We present a multi-modal dialogue system for interactive learning of perceptually grounded word meanings from a human tutor. The system integrates an incremental, semantic parsing/…
Learning how to learn: an adaptive dialogue agent for incrementally learning visually grounded word meanings
Yanchao Yu, Arash Eshghi, Oliver Lemon
We present an optimised multi-modal dialogue agent for interactive learning of visually grounded word meanings from a human tutor, trained on real human-human tutoring data. Within…
Bootstrapping incremental dialogue systems from minimal data: the generalisation power of dialogue grammars
Arash Eshghi, Igor Shalyminov, Oliver Lemon
We investigate an end-to-end method for automatically inducing task-based dialogue systems from small amounts of unannotated dialogue data. It combines an incremental semantic gram…
Challenging Neural Dialogue Models with Natural Data: Memory Networks Fail on Incremental Phenomena
Igor Shalyminov, Arash Eshghi, Oliver Lemon
Natural, spontaneous dialogue proceeds incrementally on a word-by-word basis; and it contains many sorts of disfluency such as mid-utterance/sentence hesitations, interruptions, an…