Top 7 Applications of NLP (Natural Language Processing)

In the past, did you ever imagine that you could talk to your phone and get things done? Or that your phone would talk back to you! This has become a pretty normal thing these days with Siri, Alexa, Google Assistant, etc. You can ask any possible questions ranging from “What’s the weather outside” to “What’s your favorite color?” from Siri and you’ll get an answer. All of this and more is accomplished using Natural Language Processing. And not only that, there are many other applications of Natural Language Processing these days including the translator on your phone or the grammar checker you use before sending Emails.

Natural Language Processing allows your device to hear what you say, then understand the hidden meaning in your sentence, and finally act on that meaning. And all of this is completed in 5 seconds! But the question this brings is What exactly is Natural Language Processing? And how does it work? So let’s see the answer to this first.

What is Natural Language Processing?

Natural Language Processing is a part of artificial intelligence that aims to teach the human language with all its complexities to computers. This is so that machines can understand and interpret the human language to eventually understand human communication in a better way. Natural Language Processing is a cross among many different fields such as artificial intelligence, computational linguistics, human-computer interaction, etc. There are many different methods in NLP to understand human language which include statistical and machine learning methods.

And why is Natural Language Processing important, you wonder? Well, it allows computers to understand human language and then analyze huge amounts of language-based data in an unbiased way. This is the reason that Natural Language Processing has many diverse applications these days in fields ranging from IT to telecommunications to academics. So, let’s see these applications now.

Applications of Natural Language Processing

1. Chatbots

Chatbots are a form of artificial intelligence that are programmed to interact with humans in such a way that they sound like humans themselves. Depending on the complexity of the chatbots, they can either just respond to specific keywords or they can even hold full conversations that make it tough to distinguish them from humans. Chatbots are created using Natural Language Processing and Machine Learning, which means that they understand the complexities of the English language and find the actual meaning of the sentence and they also learn from their conversations with humans and become better with time. Chatbots work in two simple steps. First, they identify the meaning of the question asked and collect all the data from the user that may be required to answer the question. Then they answer the question appropriately.

2. Autocomplete in Search Engines

Have you noticed that search engines tend to guess what you are typing and automatically complete your sentences? For example, On typing “game” in Google, you may get further suggestions for “game of thrones”, “game of life” or if you are interested in maths then “game theory”. All these suggestions are provided using autocomplete that uses Natural Language Processing to guess what you want to ask. Search engines use their enormous data sets to analyze what their customers are probably typing when they enter particular words and suggest the most common possibilities. They use Natural Language Processing to make sense of these words and how they are interconnected to form different sentences.

3. Voice Assistants

These days voice assistants are all the rage! Whether its Siri, Alexa, or Google Assistant, almost everyone uses one of these to make calls, place reminders, schedule meetings, set alarms, surf the internet, etc. These voice assistants have made life much easier. But how do they work? They use a complex combination of speech recognition, natural language understanding, and natural language processing to understand what humans are saying and then act on it. The long term goal of voice assistants is to become a bridge between humans and the internet and provide all manner of services based on just voice interaction. However, they are still a little far from that goal seeing as Siri still can’t understand what you are saying sometimes!

4. Language Translator

Want to translate a text from English to Hindi but don’t know Hindi? Well, Google Translate is the tool for you! While it’s not exactly 100% accurate, it is still a great tool to convert text from one language to another. Google Translate and other translation tools as well as use Sequence to sequence modeling that is a technique in Natural Language Processing. Earlier, language translators used  Statistical machine translation (SMT) which meant they analyzed millions of documents that were already translated from one language to another (English to Hindi in this case) and then looked for the common patterns and basic vocabulary of the language. However, this method was not that accurate as compared to Sequence to sequence modeling.

5. Sentiment Analysis

Almost all the world is on social media these days! And companies can use sentiment analysis to understand how a particular type of user feels about a particular topic, product, etc. They can use natural language processing, computational linguistics, text analysis, etc. to understand the general sentiment of the users for their products and services and find out if the sentiment is good, bad, or neutral. Companies can use sentiment analysis in a lot of ways such as to find out the emotions of their target audience, to understand product reviews, to gauge their brand sentiment, etc.

6. Grammar Checkers

Grammar and spelling is a very important factor while writing professional reports for your superiors even assignments for your lecturers. After all, having major errors may get you fired or failed! That’s why grammar and spell checkers are a very important tool for any professional writer. They can not only correct grammar and check spellings but also suggest better synonyms and improve the overall readability of your content. And guess what, they utilize natural language processing to provide the best possible piece of writing! The NLP algorithm is trained on millions of sentences to understand the correct format.

7. Email Classification and Filtering

Emails are still the most important method for professional communication. However, all of us still get thousands of promotional Emails that we don’t want to read. Thankfully, our emails are automatically divided into 3 sections namely, Primary, Social, and Promotions which means we never have to open the Promotional section! But how does this work? Email services use natural language processing to identify the contents of each Email with text classification so that it can be put in the correct section.

Conclusion

These are the most popular applications of Natural Language Processing and chances are you may have never heard of them! NLP is used in many other areas such as social media monitoring, translation tools, smart home devices, survey analytics, etc. Chances are you may have used Natural Language Processing a lot of times till now but never realized what it was. But now you know the insane amount of applications of this technology and how it’s improving our daily lives. If you want to learn more about this technology, there are various online courses you can refer to. 

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• GBlog
• NLP
• AI-ML-DS Blogs
• AI-ML-DS
• Natural-language-processing

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