The easiest way for human-kind to convey their emotions and thoughts to one another is by the means of a language. The modern world consists of thousands of languages and millions of dialects. Thing don’t quite stop here when idioms and proverbs and even slangs come into the picture.
Now, the way in which words are spoken by humans is called a “natural language”. Often, this differs from a country to country, region to region, person to person and also intra-person when they are in different states of minds.
What is Natural Language Processing (NLP)?
When a computer tries to process large amounts of data in the form of natural languages, it is termed as natural language processing. As a field of study, it originated around 1950s with Mr. Alan Turing’s article on “Computing Machinery and Intelligence” and the “Turing Test”. In this parlance, the computer has to deal with speech recognition, natural language understanding, natural language translation, natural language generation, etc.
How does NLP work?
NLP uses algorithms in order to identify and extract the natural language rules by the means of which the data is converted into binary or other computer-understandable language. With the advent of Machine Learning and Artificial Intelligence the processing of natural languages has been essential as well as easier. Hence all these technologies and processes are interdependent and help in each other’s development. There are 5 phases in the NLP including lexical (structure) analysis, sematic analysis, parsing, disclosure integration and pragmatic analysis. It is thus that the machine is able to comprehend sentiments, varying grammars in language translation, intent, and even implied meanings leading to reduction in communication barriers.
Applications
· In Banks- Usage in fraud detection and prevention of counterfeiting
· In Robotics- NLP can help a robot understand the humans better eg. Humanoids
· In Healthcare- Helping people overcome anxiety issues
· In Artificial Intelligence, Machine learning, Big Data, etc
· In Linguistics- Language translation (without changing the meaning)
· In Literature- Automatic Summarization
· In Education- Spell Check and Auto-correct
· In Personal life- Personalized outputs
· In Businesses- for better communication with consumers and their sentiment analysis
And many others…
Conclusion
In this era of globalization and mechanization, the interaction of humans with machine is the key, for which reason, Natural Language Processing is instrumental.
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