What is "natural language generation" (NLG)?

Natural language generation (NLG) is a subfield of natural language processing (NLP) focused on the capability of machines to produce human-like text. This involves using algorithms to convert structured data into readable and coherent language that resembles how humans naturally communicate. NLG systems analyze the context and content they are given and then create summaries, reports, narratives, or responses that are contextually relevant and linguistically sound.

The essence of NLG lies in its purpose: to generate text that is not only grammatical and fluent but also informative and relevant, reflecting the style and tone appropriate for the target audience. This technology is widely used in applications such as automated report generation, chatbots, and content creation, illustrating its significance in enhancing human-computer interaction through natural language.

While analyzing human emotions, speech recognition, and translation are important aspects of working with language and understanding communication, they do not define NLG. Each of these processes serves different functions within the realm of language technology, distinguishing them from the text generation focus that characterizes NLG.