NLP

A Quick Overview of Language Processing

If you are aware of Google’s latest and probably the biggest update, “BERT” update which took place a few months ago then you would probably know a little bit about the language processing. If not, then below we are explaining it in brief. We have included a brief information about natural language processing, binary system, which companies are using it and where this concept can be implemented? Travel thorough this article and get the detailed information.

What is Natural Language Processing?

In simple words, Language Processing helps a computer system to understand human languages and respond to it. Language processing belongs to the field of computer science and it uses the concept of machine learning to achieve the end result. A very popular example of natural language processing is nothing but “speech to text”. Once you understand the concept of speech to text then you would probably know about this processing.

But wait, computers can only read the binary language, right? Yes, the computer system can only understand binary values. For example, if you are writing a file name “example” in the search box then computers won’t read is as “example” but instead of that it will read it as “01100101 01111000 01100001 01101101 01110000 01101100 01100101”. When the computer system is ready with the response, it converts the binary number bank to the text so that humans can read and understand it. As the computer systems cannot read human language. If you want to explore more about the binary numbering system then you can visit here.

Importance of Natural Data Processing

Computer systems are very good at reading the structure data while the human language is far from the “structured data”. For that reason, the processing of natural data language by the computer system is important as well as difficult.

NLP

A single spelling of the word has different meanings. For example, the word “mean” has two meanings. The spelling and pronounce of these words are similar but the meaning is totally different. This similarity of words makes natural data processing a difficult task for developers.

How Does Natural Data Processing Work?

Today, NPL is used in many different ways. Starting from the voice searching to answering people’s questions and what not! If you have ever asked a question to Alexa, then you have used NPL. Apart from that the most difficult implementation of natural data processing is nothing but recognizing sarcasm. Recognizing sarcasm requires situational awareness. Making a machine understand the situation requires a lot of effort from the programmer.

Applications of Natural Data Processing?

Though NDP is difficult to process, the scientists have somehow managed to implement it on various devices. Here are some examples where NDP is used!

1) Siri and Alexa

As described above, Alexa and Siri use natural data processing to understand human language or speech. Alexa skills kit by Amazon and SiriKit by Apple provides developers interfaces, tools and docs to develop conversational modules for Apple and Siri.

2) Chatbots

You would be familiar with the chatbots if you have visited customer care online centers of large companies. The concept of chatbot also adapts to NLP. It recognizes the text values inserted by the website users and responds with the best answer. Many companies today have implemented chatbots concept and it has been proven successful for customers’ question answering quickly.

3) BERT Update from Google

As discussed above, Google just rolled out a BERT update which is said to be the biggest update in the last five years. This update helps Google to understand natural language text from the internet protocol. It was an improvement made by Google to understand a user’s search in a more detailed manner and return more accurate results. This is highly appreciated and as promised, it has also made queries processing more detailed. Along with Google, a well-known search engine Bing has also rolled out the BERT update earlier.

So, above is the basic knowledge about natural language processing. After reading this article if you have any questions then do not hesitate to ask us a question by commenting below or contacting us. We would be glad to solve your doubts.

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