Comparing dialogue strategies for learning grounded language from human tutors
Yanchao Yu, Oliver Lemon, Arash Eshghi · Edinburgh Napier Research Repository (Edinburgh Napier University) · 2016
We address the problem of interactively learning perceptually grounded word meanings in a multimodal dialogue system. Human tutors can correct, question, and confirm the statements of a dialogue agent which is trying to interactively learn the meanings of perceptual words, e.g.\ colours and shapes.We show that different learner and tutor dialogue strategies lead to different learning rates, accuracy of learned meanings, and effort/costs for human tutors. For example, we show that a learner which can handle corrections in dialogue, and its own uncertainty about what it sees, can learn meanings that are as accurate as a fully-supervised learner, but with less cost/effort to the human tutor.