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Natural Language Processing

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Pranjal Dureja


The way we express ourselves, either orally or in writing, tells a lot about who we are and how we feel at that moment. The words, tone, pitch, everything adds up to create a piece of information that we want to convey to the other person and the same is very peculiar to us. In theory, human behaviour is predictable with the help of the information a human being conveys through verbal communication.

An individual is capable of generating thousands of sentences, and each sentence has its own level of complexity attached to it. Now imagine the level of complexity in analysing the language used by crores of people. Therefore, in practice, analysing human language is not as easy as it looks.

The data generated by our conversations, both formal and informal, are examples of unstructured data. Unstructured data either does not have a pre-defined data model or is not organized in a pre-defined manner i.e. it cannot be fit into specific compartments of datasets. This is where artificial intelligence (AI) comes into the picture. With the help of machine learning, a subset of AI technology, it is now possible to detect figures of speech and even analyse sentiments. The computer adopts the cognitive way of understanding the text or speech instead of searching for keywords. This ability of the computer to understand text and speech in the same way as human beings is called Natural language processing (NLP). It makes language processing fast, effective and accurate.

The practical applications of NLP include translation of text from one language to the other (Google Translate), response to spoken commands (digital assistants like OK Google, Siri and Alexa), speech to text dictation, word processors that check grammatical accuracy (like Microsoft Word and Grammarly) etc. NLP sure holds a lot of potential in the content-driven 21st century.