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Recent Advances in Natural Language Generation: A Survey and Classification of the Empirical Literature

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Journal Article

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Slovak Academy of Sciences

Abstract

Natural Language Generation (NLG) is defined as the systematic approach for producing human understandable natural language text based on non-textual data or from meaning representations. This is a significant area which empowers human-computer interaction. It has also given rise to a variety of theoretical as well as empirical approaches. This paper intends to provide a detailed overview and a classification of the state-of-the-art approaches in Natural Language Generation. The paper explores NLG architectures and tasks classed under document planning, micro-planning and surface realization modules. Additionally, this paper also identifies the gaps existing in the NLG research which require further work in order to make NLG a widely usable technology.

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Computing and Informatics, 36(1), 1-32.

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The contents of this journal will be available in an open access format 12 month(s) after an issue is published.