Why is natural language generation important?

With Natural Language Generation, data can be assessed, analyzed and communicated with precision, scale and accuracy. With smart automation of routine analysis and related tasks, productivity surges and humans can focus on more creative, high value – high return activities.

Is NLG the same as NLP?

Natural Language Processing (NLP) is what happens when computers read language. NLP processes turn text into structured data. Natural Language Generation (NLG) is what happens when computers write language. NLG processes turn structured data into text.

Is text planning a part of natural language generation?

NLG Process On semantic models we perform text and discourse planning to generate right domain centric grammatically correct text. NLG Involves following steps: Text Planning (Templates, Rules, Scripts) Lexical Planning (Morphology, Lexical analysis..)

What is natural language generation in artificial intelligence?

Natural language generation (NLG) is the use of artificial intelligence (AI) programming to produce written or spoken narratives from a data set. The speed of NLG software is especially useful for producing news and other time-sensitive stories on the internet.

What is the future of natural language generation?

The growth of NLP is accelerated even more due to the constant advances in processing power. Even though NLP has grown significantly since its humble beginnings, industry experts say that its implementation still remains one of the biggest big data challenges of 2021. Before putting NLP into use, you’ll need data.

What does natural language generation and deep learning do to your business?

Essentially, NLG brings artificial intelligence (AI) to business intelligence (BI) by automating routine analysis, saving business users time and money. With smart automation of routine analysis and related tasks, productivity surges and humans can focus on more creative, high value-high return activities.