- Mathematical Foundations: Formal Grammars and Languages
- Finite-State Technology
- Statistical Methods: Fundamentals
- Statistical Models for Natural Language Processing
- Machine Learning
- Word Representation
- Deep Learning
- Sublanguages and Controlled Languages
- Corpus Annotation
- Text Segmentation
- Part-of-Speech Tagging
- Semantic Role Labelling
- Word Sense Disambiguation
- Computational Treatment of Multiword Expressions
- Textual Entailment
- Natural Language Generation
- Speech Recognition
- Temporal Processing
- Text-to-Speech Synthesis
- Machine Translation
- Translation Technology
- Information Retrieval
- Information Extraction
- Question Answering
- Text Summarization
- Term Extraction
- Web Text Mining
- Opinion Mining and Sentiment Analysis
- Spoken Language Dialogue Systems
- Multimodal Systems
- Natural Language Processing for Educational Applications
- Automated Writing Assistance
- Text Simplification
- Author Profiling and Related Applications
Abstract and Keywords
Communication via a natural language requires two fundamental skills: producing ‘text’ (written or spoken) and understanding it. This chapter introduces newcomers to computational approaches to the former—natural language generation (henceforth NLG)—showing some of the theoretical and practical problems that linguists, computer scientists, and psychologists encounter when trying to explain how language production works in machines or in our minds. The chapter first defines and illustrates the abstract components of the NLG task and their distinctive roles in accounting for the coherence and appropriateness of natural texts and then sets out the principal methods that have been developed in the field for building working computational systems. Current problems, new proposals for solutions and potential applications are also briefly characterized.
John Bateman is Professor of Applied Linguistics at the University of Bremen, Germany. Since obtaining his Ph.D. from the Department of Artificial Intelligence at the University of Edinburgh in 1985, he has worked in natural language generation and functional linguistics, applying the latter to the former, on projects in Scotland, Japan, California, and Germany, as well as in a variety of European cooperations. His main research focuses are multilingual NLG, multimodal document design, discourse structure, and the application of all areas of systemic-functional linguistics.
Michael Zock is Emeritus Research Director of the CNRS and is currently affiliated with University of Marseille, France (LIF-AMU). He holds a Ph.D. in experimental psychology. Having initiated (1987, Royaumont) the European Workshop Natural Language Generation workshop series, he has edited five books on language generation. His major research interests lie in the building of tools to help humans to produce language (speaking/writing) in their mother tongue or when learning a foreign language. His recent work is devoted to the navigation in electronic dictionaries, aiming at overcoming the tip-of-the-tongue problem, and facilitating the access, memorization, and automation of words and syntactic structures.
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