Nurturing the Rudiments and Use Cases of Ongoing Natural Language Generation for a Future Profitable Business More Profitable
subject: Dialogue system; Lexicalisation; Micro planning; Orthographic realization; Sentence aggregation
description: Decoding the world of artificial intelligence and its usage in the current intelligence landscape enhance bottom-up growth in building resilient global business. The areas of artificial intelligence (AI) concerned with human-to-machine and machine-to-human interaction. The Next Wave in AI-driven speech is Natural Language Generation (NLG). Natural Language Generation (NLG) is the use of artificial intelligence (AI) programming to produce written or spoken narrative from a dataset. NLG is related to computational linguistics, natural language processing (NLP) and natural language understanding (NLU). NLG research often focuses on building computer programs that provide data points with context. Sophisticated NLG software has the ability to mine large quantities of numerical data, identify patterns and share that information in a way that is easy for humans to understand. The speed of NLG software is especially useful for producing news and other time-sensitive stories on the internet. At its best, NLG output can be published verbatim as web content. The goal of Natural language generation (NLG) is to use AI to produce written or spoken narrative from a dataset. Therefore, this study aims to study how NLG enables machines and humans to communicate seamlessly, simulating human to human conversations and using NLG how organizations are building new customer experiences, monetizing information assets, introducing new offerings and streamlining operational costs. Therefore, the coverage of this chapter will answer to the industrialists and new start-ups. What can NLG do for business? and what are the future applications of NLG? 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
creator: Sivarethinamohan R.; Sujatha S.
source: Learning and Analytics in Intelligent Systems, Vol-25, pp. 149-160.
publisher: Springer Nature
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 26623447
format: Online
language: English
type: Book chapter
coverage: Sivarethinamohan R., Department of Professional Studies, CHRIST (Deemed to be University), Bengaluru, India; Sujatha S., K Ramakrishnan College of Technology, Tamilnadu, Trichy, India