Natural Language Processing: Training your computer to speak human

Traditionally computers prefer to speak in structured terms. The binary of 1’s and zeros. Tabular formats, databases, financial records. To sum it up in two words: Structured Data

Unlike us human, we are unstructured data. Communication is done using words, strings of symbols and parenthesis that to the poor computer is a jumbled mess of confusion.

This is where Natural Language Processing (NLP) comes in.

George Seif defines NLP on Towards Data Science’s website as “NLP is a sub-field of artificial intelligence that focuses on enabling computers to understand and process human languages. The goal is to get the computers to a closer human-level understanding of language.”

Natural Language Processing (NLP) is the discipline of teaching computers to read more like people, and you see examples of it in everything from chatbots to the speech-recognition software on your phone. Modern NLP techniques based on machine learning radically improve the power of software to recognize patterns, use context to infer meaning, and accurately discern intent from poorly-structured text.

In general terms, NLP breaks down language into shorter elemental pieces so that the computer can try to understand relationships between the pieces and explore how they work together to create meaning.

Some of the capabilities of NLP include

  • Content categorization
  • Topic discovery and modelling
  • Contextual extraction
  • Sentiment Analysis
  • Speech-to-text and text-to-speech conversion
  • Machine translation

The end goal is to take raw language input and use linguistics and algorithms to transform or enrich text in such a way it delivers greater value.

Next week, we will explore the uses of NLP and how CyberFlex has implemented it.

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