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Natural Language Generation

Princeton University_050622A
[Princeton University]

 

- Overview 

Natural Language Generation (NLG) is the process of producing meaningful phrases and sentences in the form of natural language. Natural language generation (NLG) is a software process that uses AI to produce written or spoken language from data. 

NLG uses machine learning and deep learning models to convert numbers into natural language text or speech. In its essence, it automatically generates narratives that describe, summarize or explain input structured data in a human-like manner at the speed of thousands of pages per second. 

However, while NLG software can write, it can’t read. The part of Natural Language Processing (NLP) that reads human language and turns its unstructured data into structured data understandable to computers is called Natural Language Understanding (NLU). 

NLG helps computers to communicate with users in a way that humans can understand. It can complete tasks such as: 

  • Language translation
  • Question answering
  • Converting unstructured data into a structured format

NLG techniques include: 

  • Aggregation: Merging similar sentences to improve readability and naturalness
  • Grammatical structuring: Applying grammatical rules to generate natural-sounding text
 


[More to come ...]



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