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Best Natural Language Processing Applications: A blog around NLP applications.

We have certainly come a long way from imagining that the future will have flying

cars and talking dogs, where evolution was certainly overhyped to talking and

commanding the non-living things on which our lives depend now for making our

day-to-day work easier. Pretty sure only a handful of people in their wildest dream

ever thought of this.

Imagine someone 20 years ago telling you on the street that he was able to talk to

his phone and his/her phone was able to talk back to him and was able to solve

problems and do work for its owner. This is very common these days with us using

Siri, Google Assistant, and Alexa. All of this is possible due to the modern phenomena

of Natural Language Processing.

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. These involve breaking down human language into its most basic pieces

and then understanding how these pieces relate to each other and work together to

create meanings in sentences.

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 very difficult for humans to

accomplish. In addition to that, there are thousands of human languages in

hundreds of dialects that are spoken in different ways by different ways. NLP helps

resolve the ambiguities in language and creates structured data from a very

complex, muddled, and unstructured source.

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 is a technique in Natural Language Processing. It allows the

algorithm to convert a sequence of words from one language to another

which is translation. 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. And not just

private companies, even governments use sentiment analysis to find popular

opinion and also catch out any threats to the security of the nation.

6. Grammar Checkers

Grammar and spelling is a very important factor when 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 tools 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. That is why it can suggest the correct verb tense, a better

synonym, or a clearer sentence structure than what you have written. Some of

the most popular grammar checkers that use NLP include Grammarly,

WhiteSmoke, ProWritingAid, etc.

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. This method is not

perfect since there are still some Promotional newsletters in Primary, but its

better than nothing. In more advanced cases, some companies also use

specialty anti-virus software with natural language processing to scan the

Emails and see if there are any patterns and phrases that may indicate a

phishing attempt on the employees.

Chances are you have never heard of these Natural Language Processing

applications! In addition to social media monitoring, translation tools, smart

home devices, and survey analytics, NLP is used in many other areas. Most

likely, you have used Natural Language Processing a lot but never realized

what it was. But now you know all the applications of this technology and how

it improves our everyday lives.

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