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Natural Language processing – A beginner’s guide

Lockdown has a lot of us available with free time which for some means streaming videos online. Recently, an old video resurfaced on Facebook, where a grandson had gifted his grandmother a Google Home device, and the grandmother was trying to use it for playing an Italian song. She didn’t even say the trigger word, ‘Hey Google’ correctly, and instead would say ‘Googoo’, which to be honest was hilarious. Google possesses the capability of conversing in Italian and many other languages. But how does it do that? Someone sitting in France can use the same device and converse with it in French, while someone else in Germany could communicate with it in German, so on and so forth. It is basically humans communicating with a machine. And the science behind that is Natural Language Processing (NLP).

Natural Language Processing is a subfield of Artificial Intelligence and Machine Learning which deals with acting as an intelligent interface between machines and humans.
A layman would not know how to converse with a machine in binary, he would use his own language. That is when NLP comes into the picture and helps humans hold conversations with smart devices. These interactions are not limited to communications, but also perform several other functionalities which makes it ideal for processing and delivering results in response to the natural human language.in fact, according to a report by Omdia, the NLP market is expected to reach $22.3 Billion by 2025.

Let us look at some of the functionalities that NLP can perform-

  1. Virtual Assistance – Businesses today have made a shift towards directing their focus on providing the best customer experiences that they can. And for that, they make themselves available at the service of their customers all the time. Businesses today are making use of NLP to create virtual assistance features for their businesses which can provide personalized help and solutions to the needs and questions of the customers. These features are open-domain and also completely automated which makes it easier to have real-time conversations and immediate grief relief.
  2. Consumer behavior insights – With the virtual world overtaking the real one, it has become difficult to analyze and figure out what is the perception of your product or how are the customers feeling about your brand through digital communications. Natural Language Processing can be implemented to the social sites of the companies and the responses, reactions, and actions of the visitors and interactors can be analyzed. This functionality can provide businesses with meaningful insights into the sentiments of their users. For example, analyzing the comments section of a post on Instagram and identifying its performance. Like said by Liang Zhou, the head of Data Intelligence at J.P Morgan, “We could convert a news article about a company into numbers that express positive sentiment and negative sentiment.
  3. Text Analysis – Natural Language Processing has the ability to analyze texts. Let’s take an example, a person talking to a machine that implements NLP says ‘open English song’, then the machine will deliver to the user a list of English songs. Here, the machine understood that open means play without the user having to explain it. Similarly, if there’s a huge thesis that needs summarization, NLP can do that by analyzing the contents and writing down the context in a short gist. Businesses are only now understanding the depth and reach of text analytics to which something stated by Meta S. Brown, the author of Data Mining for Dummies, “you will not make money on text analytics if you do not start with a plan to do it” resonates greatly.
  4. Predictions – Natural Language Processing is quite a smart technology that teaches the machines to deliver predictions. For example, you use a search engine and look for results for AI and BI, multiple times. The next time you go on to the browser and hit the search bar, it will give you predictions of topics surrounding the topic you previously looked for, AI and BI. The algorithms of NLP and text mining can be used to figure out patterns and draw inferences for the future course of action. This helps in making well-informed decisions.
  5. Deep Learning – NLP can perform advanced actions by deep learning content and accordingly deciding the steps to be taken. It is not just an overview, but an entire analysis. There are different layers within the network that act as a hierarchy for the data input and evaluation is done based on these approaches. Like when the machine sends certain emails to the spam folder, it performs deep learning to all the contents and then decides on the fact that it belongs to spam.

Natural Language Processing is quite an intriguing area of AI and ML which is tightly related to working with humans and their languages. There is a greater science involved which makes this technology a highly advanced one.

For more such updates and perspectives around Digital Innovation, IoT, Data Infrastructure, AI & Cybersecurity, go to AI-Techpark.com.

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