ThinkML - Shaip

How to Fix Natural Language Processing Challenges?

As a technology enthusiast who has 20 years of experience in AI, Vatsal Ghiya CEO and co-founder of Shaip has talked about the challenges that come with Natural Language Processing and how organizations can overcome them.

The Key Takeaway from the Article is-

  • An action might speak louder than words but words definitely determine the course of action relevant to highly intelligent machines and models. And Natural Language Processing(NLP) is the definitive approach that can make a difference in gaining insight from the data. NLP gets support from the Natual Language Language Understanding to breakdown human language into machine language.
  • Despite being used widely NLP comes with its own set of challenges like lack of context for homographs, and homophones, unclear interpretation of multiple words, errors related to text and speed, inability to fit in slang and colloquialisms lack of R& D and many others.
  • Any organization can get away with challenges by choosing the right vendor to train and develop the envisioned NLP model. Choose a vendor that offers seamless data annotation, custom assistive technologies, domain-specific databases, multilingual databases, and part-of-speech tagging capability.

Read the full article here:

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