Source: Deep Learning on Medium
What is Natural Language Processing (NLP )?
Natural language processing (NLP) is a form of interaction between humans and machines using human languages. There are many programming languages are present in nowadays. Developers learn them and work with machines. But it’s difficult for a common man to learn a computer language. So there is a step ahead to make the machine understand human language results NLP.
NLP is much important these days as it takes part in our daily activities as home/personal assistant, machine translation and recommended ads. This article covers the history, techniques, applications & modern trends in NLP. So go through this article to get a brief understanding of NLP.
The research for the NLP was started over the 60 years. Computer scientists have attempted to bring automatic systems to the machine for the understanding of human language.
From 1906–1911, the Swiss linguistics professor named Ferdinand de Saussure made research which changes the “Language as science” to language as “ systems”. He argued about contexts & meanings of the words to bring the language system in the modern approach.
In 1950, the scientist Alan Turing has brought that idea as his research paper COMPUTING MACHINERY AND INTELLIGENCE. This paper became a milestone in NLP research.
Then in 1952, the Hodgkin-Huxley model introduced the influence of neurons & electric pulses in the functioning of the brain. It let to the implementation of artificial neural networks which much helps in NLP.
With the help of these research papers, NLP tasks become easier.
To understand the NLP, we have to break down the basic techniques used to mine information from the human language. They are mostly natural linguistics such that syntax, semantics, and pragmatics.
The syntax is the grammar we used in the language. That is the components of meaningful sentences such as nouns, verbs, adverbs, etc.
Eg: I am going to work.
In the above sentence, you can observe that ing comes with go is according to grammar.
The semantics is relationships between the words when combining. That is the meaning of the words in cases such as antonymy, synonymy, and linkage between syntax.
Eg: Hero — Villian.
The relationship between the above two words is synonymy. The study about them is semantics
The pragmatics is about the context in which the words should be used.
Eg: There are many trees in the riverbank.
In the above sentence, due to the presence of the bank next to the river gives the meaning of riverside. Otherwise, when it is used alone, it will mean the place where we save money.
The way in which artificial intelligence uses these techniques to get the information from any source of human languages such as text, image or audio is actually the NLP.
The reason for the growth of NLP is its applications. NLP is used to change the way in which human talks with the machine. Nowadays the most human-related, the machine is a mobile phone and technology is the internet. So most of its application is internet or mobile-based.
- Search engine — Your daily searches in the search engines are facilitated by NLP.
- Online ads — Internet understand you by using your text gestures.
- Voice Search — NLP transforms your voice into a machine-understandable form.
- Machine Translation — All of the machine translation are based on NLP
- Voice Assistant/ChatBots — Siri, Google Assistant, Alexa are interacting using NLP
- Text Summarization — Extracting summary from an article.
These are only some of common applications of NLP. There are a lot more applications that are there. Anyhow, we have to admit that we use NLP at least once a day.
In the beginning, NLP was treated as a set of rules implemented from linguistics using traditional programming language. But the problem is languages are evolving day-by-day. Therefore traditional programming becomes not adequate in most of the NLP cases. (But, need for traditional programming still exists in serval parts of NLP)
The ultimate alternative for traditional programming is AI. The artificial intelligence’s subsets are used prominently these days for NLP such as Artificial Neural Networks. They imitate the human brain and makes the NLP more accurate. This modern approach is practiced all over the cases with the help of more computational power which is only possible in this technology era.
NLP is a modern approach to make interactions with humans and machines easier. NLP researches have already started long ago. Natural Linguistics techniques are used in NLP. Applications of NLP are wide and take part in our daily life also. Artificial intelligence is used in
This article is a brief introduction and I will continue deeply into NLP in upcoming blogs. Any more thoughts about this article? I’m free to hear from your comments.