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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