An application of Artificial Intelligence that is used to interpret human language by AI machines, Natural Language Processing is a widespread AI application in the 21st century.
One of the fundamentals that have driven technological advancement to the stage where it is today, Natural Language Processing or NLP has made human intelligence understandable.
Through a set of machine learning algorithms, or deep learning algorithms and systems, NLP had eventually made data analysis possible without humans. The significance of Natural Language Processing in linguistics is immense, and NLP has been in existence for over half a century.
It has advanced to such a level that machines everywhere are now using this technology to analyse data and carry out other functions as well. With humongous quantities of unstructured and unorganized data, NLP has helped big businesses to filter data and organize it well.
(Must check: Top 12 NLP Libraries in Python)
Natural Language Processing can be understood in light of NLP applications that are all around us. From messaging with companies to typing on our smartphones, NLP is omnipresent.
Let us now move on to understanding the concept in a better manner with the help of its applications. Some of the Natural Language Processing examples are given below.
Auto-correction/Auto-completion of words, Source
While typing on your smartphone, do you ever realize how your keyboard auto-corrects the words that you type? Or even when it auto-completes your words that you are about to type?
Well, NLP is the magic behind auto-correction and auto-completion of words on your keyboard. The feature of auto-correction and auto-completion lets you rectify your mistakes and beforehand and lets your search results be on point!
Even when you type a word incorrectly and Google displays the correct version of your search input, NLP is doing its job in the background which ultimately means that it interprets human language and helps analyse the data correctly.
You read it right! One of the best examples of Nlp is the recruitment process that is used all around the world on a day-to-day basis. From big businesses to small-scale industries, everyone relies on the recruitment process to hire potential professionals in order to run their company and earn profit in the long run.
NLP steps into this process as it filters various candidates on the basis of their experience, job requirements, etc. Extensively used in this case, NLP relies on the technique of information extraction and helps a panel of recruiters to hire the best candidates for a certain job.
How much time does it take you to use the Google Translator and find the meaning of a french word? Less than a minute, right? Well, NLP uses the technique of Machine Translation that relies on its ability to convert the meaning of a word in one language into another.
That is the reason why humans can easily and readily fetch the meaning of any word in any language in an instant, thanks to NLP. With global connectivity trending right now, the technique of natural language translation is a much needed tool that we need for various purposes.
language translate-google, Source
From interpreting the meaning of a foreign language song to doing a project in another language, NLP readily fetches the meaning of one word and presents it in the chosen language of the user, perhaps serving the purpose.
Chatbots, or chatting robots have become the norm. With everything being computerised, robots have now taken up the job of communicating with humans through screens in order to solve their grievance.
This technology too is powered by Natural Language Processing. With the help of a set of algorithms, robots can communicate with humans and get things done in no time. For instance, an example of a chatbot application is uber is supported by AI and serves its customers through ML chatbots.
From booking a cab to filing a feedback, customers are served by robots that are computerised and have the ability to interpret human language. Chatbots have become a revolutionary step in the realm of technological advancement as they have left behind the human race when it comes to communication.
Ever wondered how your email filters all your mails and marks some mails as 'spam'? Spam notifications are another example of NLP that uses the technique of identifying some words or sentences that can indicate a spam message. Spam notifications have become an extremely necessary component when it comes to emails.
While a lot of mails are important, some others tend to waste our time and so, NLP helps to filter these mails and tag them as spam. This helps us in identifying these mails as spam so we know that we should not click on these. Undoubtedly, NLP is a boon for the digital world.
Moreover, it also saves us from being cheated on which is a major threat to cyber security in the modern scenario.
"Hey Alexa, please explain how NLP is used in voice assistants."
The world has increasingly adapted to voice assistants like Alexa and Siri who operate on the basis of Natural Language Processing.
Thanks to NLP, voice assistants like these have made our lives a bit easier. From reciting poems for our infants to calling someone as soon as we command them to do so, Alexa and Siri really deserve a big applause!
Yet the background work is done by NLP that makes use of AI and interprets human language with the help of linguistics. This further helps it to accelerate technological advances like it has done in the case of voice assistants.
Now, from commanding Google voice assistant to search for a famous cafe near you to asking Siri why heartbreak is so painful, one can do almost anything and voice assistants will surely never leave his/ her way!
Another application of NLP is social media surveillance. Do you ever think of how social media platforms like Instagram and Facebook analyse an account's performance?
How does a brand analyze if it's social media marketing stints are influencing the netizens or not? The answer is NLP.
Social media surveillance involves monitoring social media performance, looking for potential loopholes, collecting feedback from the audience, and responding to them diligently.
This is where NLP does its work and helps one in analyzing a social media handle's performance and impact overall. Furthermore, it helps in filtering the information collected and working on it accordingly.
Technology has come so far that machines call us in humanly voices to solve our problems. Calling customer care is all about computerised voices connecting you to company officials!
However, have you ever thought of how this is even possible? NLP is the solution to this question. Computer- generated calling is another example wherein NLP does its work flawlessly.
From customer cares to company contact numbers, customers deal with NLP-based machines that converse in as humanly voices as possible. This alone is a wonder of the world where robots are commanding the way humans work more than ever.
Big Data analytics is a field that involves analysing data that is humongous and unorganized as well. Ever since technology has played its magic over the field of data analytics, data has become much more easy to collect, store, and analyze.
NLP further eases this process by taking help of various algorithms that together help in analysing data on the basis of various grounds. From filtering data for names of employees to organizing data on the basis of different departments in a firm, NLP analytics has assisted humans to carry out the process of data analytics for over half a century.
In addition, Business Intelligence and data analytics has triggered the process of manifesting NLP into the roots of data analytics which has simply made the task more efficient and effective.
While writing a project or even an answer, we often get conscious of our grammar and the language we use. So, we turn towards grammar checking tools that help us rectify our mistakes in no time and further help us analyze the strength of our language with the help of various parameters.
All this is facilitated by the technological advancement of Natural Language Processing that helps applications to insert language that in turn makes it possible for professional grammar checker tools to analyse our content.
Therefore, the credit goes to NLP when your project is rated 10/10 in terms of grammar and the kind of language used in it! For instance, grammarly is a grammar checking tool that helps one to run through their content and rectify their grammar errors in an instant .
To conclude, Natural Language Processing has become a part of our digital lives. Believe it or not, our lives somehow rely on NLP as it is present everywhere facilitating our day-to-day chores.
(Must check: Top NLP Trends for 2021)
Moreover, NLP is a tool of AI that will only help the realm of technology to advance and excel in the forthcoming time. The future of NLP is expected to be brighter as more and more applications of NLP are becoming popular among the masses. With respect to its tools and techniques, NLP has grown manifold and will likely do so in the long run.
Reliance Jio and JioMart: Marketing Strategy, SWOT Analysis, and Working EcosystemREAD MORE
6 Major Branches of Artificial Intelligence (AI)READ MORE
Top 10 Big Data TechnologiesREAD MORE
8 Most Popular Business Analysis Techniques used by Business AnalystREAD MORE
7 types of regression techniques you should know in Machine LearningREAD MORE
Deep Learning - Overview, Practical Examples, Popular AlgorithmsREAD MORE
Introduction to Time Series Analysis in Machine learningREAD MORE
How Does Linear And Logistic Regression Work In Machine Learning?READ MORE
What is the OpenAI GPT-3?READ MORE
7 Types of Activation Functions in Neural NetworkREAD MORE