This paper provides a comprehensive analysis of the first shared task on End-to-End Natural
Language Generation (NLG) and identifies avenues for future research based on the results …

Recent advances in corpus-based Natural Language Generation (NLG) hold the promise of
being easily portable across domains, but require costly training data, consisting of meaning …

Medical decisions directly impact individuals' health and well-being. Extracting decision
spans from clinical notes plays a crucial role in understanding medical decision-making …

We present and evaluate a novel approach to natural language generation (NLG) in
statistical spoken dialogue systems (SDS) using a data-driven statistical optimization …

We present “conversational image editing”, a novel real-world application domain
combining dialogue, visual information, and the use of computer vision. We discuss the …

Questions and answers play an important role in spoken dialogue systems as well as in
human-human interaction. A critical concern when responding to a question is the timing of …

In this paper, we present a user study where a robot instructs a human on how to draw a
route on a map, similar to a Map Task. This setup has allowed us to study user reactions to …

Stochastic natural language generation systems that are trained from labelled datasets are
often domain-specific in their annotation and in their mapping from semantic input …

Our goal is to explore how the abilities brought in by a dialogue manager can be included in
end-to-end visually grounded conversational agents. We make initial steps towards this …

Surface realisations typically depend on their target style and audience. A challenge in
estimating a stylistic realiser from data is that humans vary significantly in their subjective …