📮 Natural Language Generation by Ehud Reiter (.ePUB)+

In late 2022, the prominence of Natural Language Generation (NLG) surged with the advent of advanced language models like ChatGPT. While these developments have captivated both academic and commercial sectors, the focus has predominantly been on the latest innovations, often overlooking the rich history and foundational work in NLG. This book aims to provide a comprehensive overview of NLG, encompassing not only language models but also alternative approaches, user requirements, evaluation methods, safety and testing protocols, and practical applications. Natural Language Generation systems use Artificial Intelligence (AI) and natural language processing (NLP) techniques within software systems that generate texts in human languages such as English, Chinese, and Arabic. In other words, NLG is the science of AI systems that can write. As such it is related to (but not the same as) Natural Language Understanding (NLU), which is the science of AI systems that can read and extract meanings from human-written texts. Natural Language Generation has recently become more prominent because of the success of ChatGPT and other generative language models, but the field has been around for decades. AI and NLP techniques such as Machine Learning and language models are widely used, but they do not tell the whole story.

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