Recent Advances in Natural Language Generation: A Survey and Classification of the Empirical Literature
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 the...
| Main Authors: | , |
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| Format: | Others |
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Slovak Academy of Sciences,
2017-07-26T22:18:42Z.
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| Online Access: | Get fulltext |
| Summary: | 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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| Item Description: | Computing and Informatics, 36(1), 1-32. 1335-9150 |