Do you know there is a branch in the area of artificial intelligence that enables computers in comprehending, interpreting, and manipulating human language? It is called Natural language processing (NLP) and it attempts to bridge the gap between human communication and machine comprehension. NLP takes cues from a variety of fields, including computer science and computational linguistics for efficiency. NLP allows computers to process human language in the form of text or speech data and & interpret & its full meaning, along with the speaker's or writer's intent and sentiment. In short, NLP aims at building machines that interpret and respond to text or voice data in the same manner that humans do—and respond with text or speech of their own. Though NLP is considered a branch of Computer Science or AI, the concept of ‘language’ as ‘science’ was introduced by the Swiss linguist and Professor Ferdinand de Saussure. He also developed the idea of categorising languages as systems. Later, this structuralist approach to language expanded to computer science as well. Alan Turing and Noam Chomsky were the other two scholars who made significant contributions to the realm of NLP. In 1950, Alan Turing published a paper suggesting a test for a "thinking" machine and Noam Chomsky in his book Syntactic Structures, published in 1957 proposed that in order for a computer to grasp a language, the sentence structure must be altered.
NLP’s application is in almost everything we do in our day-to-day life and it is very easy to recognise if one understands that the basic application of NLP is for human and machine communication through text or speech or both. When you google something, it is NLP that makes the autocorrect or autocomplete. The case is the same while drafting an email or writing something on social media. Translating from one human language to another literally or contextually using a machine utilises NLP. Companies use NLP to conduct surveys among a huge population or connect to their customers through ‘chatbot’ apps or websites for solving general queries through automated replies. Do you know voice assistants like Google Assistant, Apple Siri, Amazon Alexa also employ NLP? Some other applications of NLP include filtering emails into spam, primary, social, and promotions categories, making recruitment easy by filtering resume, checking grammar and spelling, monitoring social media or targeting you with ads by analysing the ‘language’ you used, analysing your ‘sentiments’ as negative, sad or hopeful, etc with the help of the words you use. Some of the popular are Natural Language Processing Tools are IBM Watson, Amazon Comprehend, Google Cloud NLP API MonkeyLearn, Aylien, etc.
