Content Planning

This paper presents an architecture for the generation of spoken monologues with con- textually appropriate intonation. A two- tiered information structure representation is used in the high-level content planning and …...

We present a novel approach to Informa- tion Presentation (IP) in Spoken Dialogue Systems (SDS) using a data-driven statis- tical optimisation framework for content planning and attribute selection. First we …...

In a language generation system, a content planner selects which elements must be in- cluded in the output text and the ordering be- tween them. Recent empirical approaches per- form …...

AbstractLong-form narrative text generated from large language models manages a fluent impersonation of human writing, but only at the local sentence level, and lacks structure or global cohesion. We posit …...

AbstractNeural table-to-text models, which select and order salient data, as well as verbalizing them fluently via surface realization, have achieved promising progress. Based on results from previous work, the performance …...

AbstractWe study the task of long-form opinion text generation, which faces at least two distinct challenges. First, existing neural generation models fall short of coherence, thus requiring efficient content planning. …...

AbstractWe present a method for generating comparative summaries that highlight similarities and contradictions in input documents. The key challenge in creating such summaries is the lack of large parallel training …...

AbstractPoetry generation, and creative language generation in general, usually suffers from the lack of large training data. In this paper, we present a novel framework to generate sonnets that does …...

AbstractTable-to-text generation aims at automatically generating text to help people conveniently obtain salient information in tables. Recent works explicitly decompose the generation process into content planning and surface generation stages, …...