Natural Language Generation

TL;DR

This book offers a comprehensive overview of Natural Language Generation, covering foundational concepts, methodologies, evaluation, and applications, emphasizing enduring principles over recent large language model innovations.

Contribution

It consolidates decades of NLG research and practical insights, providing a broad, concept-focused resource for applied NLG practitioners and researchers.

Findings

Covers rule-based, machine learning, and neural NLG techniques

Discusses evaluation, safety, and maintenance of NLG systems

Includes practical examples and anecdotes from the author's experience

Abstract

This book provides a broad overview of Natural Language Generation (NLG), including technology, user requirements, evaluation, and real-world applications. The focus is on concepts and insights which hopefully will remain relevant for many years, not on the latest LLM innovations. It draws on decades of work by the author and others on NLG. The book has the following chapters: Introduction to NLG; Rule-Based NLG; Machine Learning and Neural NLG; Requirements; Evaluation; Safety, Maintenance, and Testing; and Applications. All chapters include examples and anecdotes from the author's personal experiences, and end with a Further Reading section. The book should be especially useful to people working on applied NLG, including NLG researchers, people in other fields who want to use NLG, and commercial developers. It will not however be useful to people who want to understand the latest LLM technology. There is a companion site with more information at https://ehudreiter.com/book/