A brief review of Natural Language Processing (NPL)

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Natural language processing allows computers to read text, listen to the speech, interpret it, gauge sentiment, and determine which parts are important. ​This article discusses Natural language processing with applications, its importance, and market value.

What is Natural Language Processing?

Natural language processing, or NLP, is a field of Artificial Intelligence that deals with how to program computers to process and analyze natural language data. Natural language processing combines computational linguistics—rule-based modeling of human language—with statistical and machine learning models. 

Natural language processing is used for a wide range of applications, including – Smart assistants, Search results, Predictive text, Language translation, Digital phone calls, and Text analytics.

Natural language processing began in the 1950s [1]. Alan Mathison Turing published his article titled “Computing Machinery and Intelligence” in 1950, which is now known as the Turing test as a criterion of intelligence [2]. Symbolic NLP is well-summarized by John Searle.

“Language is an archaeological vehicle… the language we speak is a whole palimpsest of human effort and history.” — Russell Hoban

Why is Natural Language Processing​ Important?

Natural Language Processing is a subfield of artificial intelligence that permits computers to comprehend natural language. Using NLP, machines can understand unstructured online information so that we can gain significant insights. To some, it’s a recently emerged vast body of knowledge. To others, it’s a laboratory—a rudimentary cognitive ability—and its relationship to thought.

Today’s machines can analyze more language-based data than humans can without fatigue and in a consistent, unbiased way. They are considering the staggering amount of unstructured data generated daily, from medical records to social media.

“The voice that navigated was definitely that of a machine, and yet you could tell that the machine was a woman, which hurt my mind a little. How can machines have genders? The machine also had an American accent. How can machines have nationalities? This can’t be a good idea, making machines talk like real people, can it? Giving machines humanoid identities?” ― Matthew Quick

How are growing global Natural Language Processing markets?

According to Straits Research [3], the global Natural language processing market value was USD 13.5 billion in 2021. It is expected to reach USD 91 billion by 2030, registering a compound annual growth rate of 27.1% from 2022 to 2030. 

“If literature were nothing more than verbal algebra, anyone could produce any book by essaying variations. The lapidary formula ‘Everything flows’ abbreviates in two words the philosophy of Heraclitus: Raymond Lully would say that, with the first word given, it would be sufficient to essay the intransitive verbs to discover the second and obtain, thanks to methodical chance, that philosophy and many others. Here it is fitting to reply that the formula obtained by this process of elimination would lack all value and even meaning; for it to have some virtue we must conceive it in terms of Heraclitus, in terms of an experience of Heraclitus, even though ‘Heraclitus is nothing more than the presumed subject of that experience. I have said that a book is a dialogue, a form of relationship; in a dialogue, an interlocutor is not the sum or average of what he says: he may not speak and still reveal that he is intelligent, he may emit intelligent observations and reveal his stupidity. The same happens with literature; d’Artagnan executes innumerable feats and Don Quixote is beaten and ridiculed, but one feels the valour of Don Quixote more.” ― Jorge Luis Borges

TechGolly editorial team led by Al Mahmud Al Mamun. He worked as an Editor-in-Chief at a world-leading professional research Magazine. Rasel Hossain and Enamul Kabir are supporting as Managing Editor. Our team is intercorporate with technologists, researchers, and technology writers. We have substantial knowledge and background in Information Technology (IT), Artificial Intelligence (AI), and Embedded Technology.

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