Natural Language Processing: New Era of Human-Computer Relations

This may not come across as obvious, but Natural Language Processing (NLP) is already making our lives much simpler. Whereas ten years ago there was only one option to find an answer to your query in the search results, now there is an alternative - to ask Alexa, for example. She’s great when you’re starving and don’t have the extra ten minutes to search for the nearest pizza place. And she’s polite.

In a nutshell, NLP is a computer science that makes computers capable of understanding human language, analyzing it and performing actions accordingly. NLP is now widely used in fields like speech processing, sentiment analysis, information retrieval and extraction, machine translation and many others.

In the last couple of years, there’s been a huge rise in the development of NLP technology, and for a good reason. The application of NLP has significantly increased the volume and value of insights in data analytics by adding efficiency to search, chatbots and voice user interface.

The Future of NLP: Smarter search

Not much has changed since the time when search engines came alive: they are still a trusted source of information to which users turn whenever they need an immediate answer. However, the results we receive in response to our queries are looking somewhat different to what they used to be ten years ago. Type in ‘the nearest pizza’ and Google will automatically identify your location, provide you with a list of well-rated pizza places nearby and even give you a number to call with one click.

Applying NLP technology to search engines will make them even smarter. Whereas now we tend to search by entering keywords or topics, soon the focus will shift towards the ‘search-like-you-talk’ user experience. Google has recently added NLP capabilities to its Google Drive, allowing users to search for documents using their voice. With technology such as question answering systems, targeted e-commerce searches and intelligent digital assistants developing at a rapid pace, the future of search is looking incredibly promising.

Moreover, applying NLP to search allows intuitive, google-like search experience when you work with structured data. Data can be explored just by giving natural language commands instead of filtering, browsing categories and adjusting search settings. A great thing about this novelty is that it can be applied to any kind of database, whether it contains employee records or a company’s inventory.

Understanding User Intent: the Chatbot Revolution

Chatbots are a great way to present information to consumers as quickly as possible. Instead of having to sift through endless content, users can type in their question and get a response immediately. This is made possible by applying NLP technology to bots.

The traditional example of NLP within a chatbot that almost everyone is familiar with is self-service tasks, like personal banking. Another application of NLP is focused on assisting customers with finding the right product or service via conversation. Let’s say you are looking for a piece of clothing, like ‘red linen trousers’: once your query, or intent, is received by the bot, it will then check whether it matches the shop’s inventory. Such bots can help users find the right products, vacations, movies and songs, preparing a solid ground for them to make a purchase.

Human intents are endless, and having a bot interpret the whole scope of them would be just impossible. However, applying natural language processing to bots ensures a more personal experience for users.

In practical terms, chatbots are already helping businesses increase their efficiency by providing human-like interaction with data for employees when working with internal databases. Let’s say your company has a huge sales department and you want all the members of the sales team to be able to retrieve sales stats from the database. In this case, having a chat bot that would provide all your staff with an immediate access to the database, seems like the perfect solution.

The Most Intuitive Way Possible: Voice User Interface

To see NLP in action, take a look at Voice User Interfaces that help people control computers usingtheir voice. A great example is Amazon’s Alexa - an intelligent personal assistant that enablescustomers to interact with devices in the most intuitive way possible. If you want to catch up on theprogramme you’ve missed and find out about the events taking place around the world, ask the machine.

Just like chatbots are growing smarter and learning from their previous conversations with users, so do VUIs by learning the user’s speech patterns and even building their own vocabulary.

So what puts voice technology in such high demand? The answer is obvious. For humans, voice is the most natural form of communicating a message. With voice technology, we don't even need to learn how to use it. We welcome voice experiences because we are naturally tuned to speech. Who would have thought that asking Alexa to play the latest Depeche Mode album is times quicker than searching for one yourself and then pushing a few buttons to play it?

With VUI technology becoming more robust and intelligent with each passing day, its application will naturally be extended onto mobile, cars, wearables and virtual reality, allowing us to stay connected to our needed data 24/7, no matter where we are.

What’s Next

The new era of human-computer relations has started. People no longer need to adapt to computers because computers can now adapt to their requirements. According to Gartner, by 2020, half of analytical queries will be generated using natural language or voice-based search. And Natural Language Processing is in Gartner's TOP 10 Strategic Technology Trends in 2017. There are already several products on the market. That do this kind of “magic”, among them is FriendlyData - a pioneering API-based Natural Language Processing solution for databases. FriendlyData’s API translates natural language into SQL requests and generates structured, intelligible responses. With FriendlyData one can build the advanced NLP interface directly into enterprise BI, Analytics, CRM or data warehousing solution.

It is yet to be seen what NLP’s next great leap forward is going to be. What can be said for sure is that its impact will only increase and remain positive, making our lives simpler and leaving us more time for great things.

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