Survey of the State of the Art in Natural language Generation: Core tasks, applications and evaluation

A. Gatt, E.J. Krahmer

Research output: Contribution to journalArticleScientificpeer-review

481 Citations (Scopus)

Abstract

This paper surveys the current state of the art in Natural Language Generation (NLG), defined as the task of generating text or speech from non-linguistic input. A survey of NLG is timely in view of the changes that the field has undergone over the past two decades, especially in relation to new (usually data-driven) methods, as well as new applications of NLG technology. This survey therefore aims to (a) give an up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organised; (b) highlight a number of recent. research topics that have arisen partly as a result of growing synergies between NW and other areas of artificial intelligence; (c) draw attention to the challenges in NLG evaluation, relating them to similar challenges faced in other areas of NLP, with an emphasis on different evaluation methods and the relationships between them.

Original languageEnglish
Pages (from-to)65-170
Number of pages106
JournalJournal of Artificial Intelligence Research
Volume61
Issue number1
DOIs
Publication statusPublished - 2018

Keywords

  • AUTOMATIC-GENERATION
  • CONTEXT
  • DIALOGUE
  • DISCOURSE
  • INFORMATION
  • LEXICAL CHOICE
  • MODELS
  • REFERRING EXPRESSIONS
  • TEXT GENERATION
  • WEATHER FORECASTS

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