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

• Main Authors: Perera, R (Author), Nand, P (Author)
• Format: Others
• Published: Slovak Academy of Sciences, 2017-07-26T22:18:42Z.
• Subjects: Natural Language Generation; Natural Language Processing; Lexicalization; Journal Article
• Online Access: Get fulltext

 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.