Natural Language Processing (NLP) is a type of artificial intelligence that deals with the interactions between computational systems and human (natural) languages. It works by first analysing the text input and then applying meaning to it. Few years ago it was a topic of interest among only a few computer scientists and linguists. But with the emergence of artificial intelligence it became an important part in many industries. It can be used to analyze the contents of a sentence and find out the word types, patterns, sentiment analysis and even identify key phrases or concepts in text. NLP has been applied to many fields such as financial services, healthcare, customer service and more.
Where does NLP show up in our lives and why is it useful
NLP is in more places you can think of. You can find solutions based on NLP in the healthcare sector, for example in the medical diagnosis module. There are systems that let patients input data about their symptoms, and these systems use NLP to interpret the data.
Another interesting application of natural language processing is in customer service. For instance there are chatbots that provide automated support for customers who can’t find what they need on a company’s website or contact center pages.
Chatbot also has access to databases and so it can present the customer with a detailed answer to their questions. It is incredibly helpful since support teams have limited capacity to answer emails, and it could leave some customers without help or they would be angry at long waiting times. NLP based support chatbots solve the problem.
Furthermore we can mention autonomous driving car that relies on language processing capabilities: speech recognition software recognizes commands from the driver and translate them to action, e.g., accelerate or brake the car; it’s also able to detect errors in pronunciation of commands given by a driver (e.g., “turn left” instead of “right”). Autonomous cars are still quite controversial, because they need to be taught how to make decisions in crash tests such as dilemmas to save users or people outside in a situation when there is no safe option for everyone.
In banking and financial services it is used to detect frauds or money laundering schemes. NLP can be also found as a part of customer service solutions like chat bots that help you solve your problems without human intervention.
If you have a smartphone, you can probably use a virtual assistant on it. Virtual assistant is a kind of chat-bot that can do things like sending emails, set up reminders and answer your questions about the weather.
Another application area for NLP are educational technologies: intelligent tutoring systems or digital learning environments use natural language processing algorithms to extract information from student’s input (e.g., answers on multiple choice tests).
For Internet users and especially for digital marketing and social media marketing, NLP is used for sentiment analysis. System reads the mention of a particular brand, and the sentences around it to understand the sentiment. The system then assigns a score to the brand, in order to help marketers understand how they are doing at satisfying their customers and potential consumers. There are still issues with sarcasm and irony, since NLP systems understand them in a direct way.
Future of NLP Solutions
There are plans to implement NLP in more places and to improve existing solutions. For example, Google is working on a Gmail plugin that will automatically read out the contents of emails. This means someone can hear an email message without ever opening it or reading any text from the screen – they just need to click “play” and their computer or phone will speak for them.
NLP systems can be taught to understand what is being said in a video clip, and can then translate this into text. So, there will be no need to hire a transcriber in order to have a text connected with video.
We have already talked about customer service solutions, but the future holds more for us. NLP will be used as a part of voice user interfaces, chatbots, but more deeply and specific
Chatbot scenarios:
– A customer service chatbot that can answer typical questions about the company’s products or services in real time without a need to put the client on hold
– A chatbot that can identify emotions and respond with necessary empathy, thereby improving customer satisfaction. Many don’t like to solve their problems through chatbot, because they don’t like this lack of other human who can understand their anger.
– A bot for scheduling meetings and appointments with people inside the organization – it could also be used by customers to schedule meetings outside your company. That will limit the number of emails filling inboxes since many of them are connected with scheduling. This will be also helpful for people who often forget to schedule a meeting, forget the dates of all the meetings and get lost with the number of them. Chatbot can be synchronized with Google Calendar and automatically set reminders for particular events.
Conclusion
NLP solutions are already all around us and they will only grow in their importance. They are the perfect way to go for companies who are already interested in collecting and analyzing data, but just need a little push to be able to make sense of unstructured text.
Natural language processing is a powerful tool that can bring great benefits from another perspective as well – by helping people communicate with computers more naturally, without a need to hire people for that.
It may cause some problems since many people work in customer service and support teams and it will be necessary to find new jobs for them. But we’re not there yet and until that time, it is worth giving a try and see how everyone can benefit from NLP solutions.
