7 applications of natural language processing that shape our future
Applications of natural language processing NLP
The next-gen technologies are invading our world. With the infinite amount of info and content that companies are dealing with, data analysis has become core to every business. AIML saved our research path and made us learn that machines can do the job of interpreting and extracting value from mountains data. Natural language processing known as NLP is among the elevators that help companies relate human and machine forces together.
In this blog we are evoking concrete examples of applications of natural language processing in helping businesses achieve competitive advantage but before we dig deeper let’s define what is natural language processing in software development.
What is natural language processing in software development?
Natural language processing is a field of artificial intelligence technology that enables computers to interact with human languages, from identifying and reading to concretely understanding both spoken and written language. It includes sophisticated spoken word recognition, automatic translation of one language into another, and even the capacity to answer questions in every language possible.
Most popular applications of natural language processing
No one predicted that natural language processing could evolve this powerfully to impact all kinds of industries. Here are concrete applications of this technology to understand its impact on our lives, we need to take a look at its applications.
Grammar Checkers and auto-correction
As a professional content writer, I cannot imagine my life without grammar correction apps! Thanks to natural language processing, Grammar Checking tools like Grammarly can help us write correct content and deliver emails at work without any embarrassment!
Sophiscating searching engines with auto-complete
Don’t you love how google predicts your research from just typing a few initial letters? Even when you type nonsense wrong words it would still try to correct them and formulate a relevant meaning out of them to give the best results.
We should be so grateful to NLP for allowing our search engines to be this smart to help us with what seems an easy task. Search autocomplete and autocorrect both help us in finding accurate results much efficiently and now it is more and more implemented in website research tools to help us fasten up our research.
Imagine a world without google translator and other similar tools? Be honest how many times a day you have to use a translator to complete work, research, school tasks, or even just to read a foreign post on social media? The fast smart way that NLP translates a piece of text in one language to another in a second is just behind helpful to the human race.
Beyond just easily converting text from one language to another, NLP driven translator is now able to read every word in its exact original language accent and even detect language through voice-overs
It is a blessing that is helping humanity, businesses and schools overcome language barriers
Analyzing social media posts
NLP techniques can even interfere in helping businesses analyzing social media posts to get useful insights about what clients think of them, understand the issues and problems that their customers are facing by using their products. It is even used by government security to identify potential threats related to national security and Facebook uses it to catch hateful, misogyny, racist comments and delete them.
Chatbots are there to help companies achieve the best customer experience 24/7. Unlike his human fellows, a chatbot takes no rest and never stops learning! Today’s chatbots are even used as personal companions and online psychologists; it is all possible thanks to NLP technology!
Survey results analysis and CV filtering
Conducting surveys can lead to the gathering of huge data size. It becomes impossible for a person to read them all and draw a conclusion. This is where natural language processing interferes in analyzing answers and generates useful insights from them in no time. It is so smart that it can detect the feeling of the questioned person toward a product or a company by the kind of vocabulary he is using.
It is also highly used to filter numerous CVs when people apply for a position. With entity recognition, we can extract information such as skills, name, location, and education of the candidate As it is impossible for HR people to identify potential CVs in thousands of applications.
A voice assistant is a software that uses speech recognition, natural language understanding, and natural language processing to understand the verbal commands of a user and perform actions accordingly. It just exploded our classic world of “typing” and created the famous Apple Siri, Google Assistant, Amazon Alexa, etc that we love.
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Data is what made the world we know. We can never have enough of using data for business purposes. The applications above are only a few compared to the huge potential of natural language processing. Thanks to NLP implementation within organizations, we can analyze available data deeper, enhancing our business efficiency and communicating our business services intelligibly.