Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation
Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation
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DOI：
10.1613/jair.5477
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发表时间：
2018-01-01
影响因子：
5
通讯作者：
Krahmer, Emiel
中科院分区：
文献类型：
--
作者：
Gatt, Albert;Krahmer, Emiel
本文综述了自然语言生成的现状，自然语言生成的定义是从非语言输入生成文本或语音的任务。鉴于过去二十年来该领域发生的变化，特别是与新的(通常是数据驱动的)方法以及NLG技术的新应用有关的变化，对NLG进行调查是及时的。因此，本调查的目的是：(A)提供关于国家联络小组核心任务和组织这些任务所采用的架构的最新研究综述；(B)突出最近开展的一些活动。(C)提请注意NLG评价方面的挑战，将它们与NLP其他领域所面临的类似挑战联系起来，重点放在不同的评价方法及其之间的关系上。
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.