An overwhelming number of apps are leveraging Natural Language Processing (NLP) technology these days as it helps mine useful information from the apps.The use of NLP in mobile app development makes the app smarter as it mechanically analyzes the text data and voice data and derives meaning out of it, and even takes required actions on behalf of mobile users. Lets see How Natural Language Processing Powers Mobile Apps.
What’s Natural Language Processing in Nutshell?
Natural Language Processing, NLP, a branch of artificial intelligence, enables computer programs to decipher and make sense of human language, which may be in written or text format. The system extracts meaning from an input of sentences, paragraphs, pages, etc., and takes appropriate steps on behalf of mobile users.
Some famous NLP examples are Siri from Apple, Ok Google from Google, and Cortana from Microsoft.
Apps using Natural Language Processing
- Google Translate – a language translation application that uses NLP.
- Siri, Cortana, Alexa, and Ok Google – all personal assistant apps use NLP.
- Apps used in call centers known as Interactive Voice Response also use NLP.
How does Natural Language Processing Work?
NLP uses algorithms to convert unstructured language data into understandable computer language. Once the text is extracted, its meaning is derived to find the essential data from them.
Natural Language Processing in Mobile Apps
NLP technology is a progressive technology, better than virtual assistants. Mobile app developers integrate NLP to make mobile app devices convenient for people with physical disabilities.
Businesses are devising advanced solutions for mobile app development employing Machine Learning and NLP. These solutions aim to aid users in formulating questions in ordinary language and receive answers in the same way.
The use of NLP is becoming widespread in mobile apps with spam-related issues.
1. NLP Powering Information Engine
As it turns out, Google will soon be employing NLP-based technology in mobile devices to offer better results. By far, virtual assistants can find answers to your basic questions successfully. From now on, it will be able to answer complicated questions with the aid of NLP.
Further, NLP is good when it comes to pulling out information from information stores. Who knows, future information engines could be employing websites, ebooks, videos, and television footage with absolute accuracy with NLP’s aid to compile massive databases with 100% accuracy. Such a finding could usher in a new era as to how people absorb and utilize information.
Plus, NLP technology has profound uses in the area of prediction as well. For instance, it can be used for predicting political and social events, and even terrorism threats could be found out by checking online and phone-based chatter. Even language translation apps might go through a huge transformation process. If you plan to build a mobile app integrated with NLP, browse GoodFirms list to hire India app developers.
2. NLP Powering Mobile Apps in Medical Field
NLP is commonplace in the medical and healthcare sector. With hands-free communication becoming the norm, the apps that are part of wearable health equipment use verbal input over typing.
Here are a few of the applications of NLP technology in the health care sector.
Note Taking: Patients, most often than not, fail to take all the information that a physician discusses at an appointment. The NLP technology can be used to take down notes directly from the physician’s speech. The notes could be in the form of tips, names of medicines, dosage information, and more.
Verbal Updates & Input: A surgeon, while conducting a surgical procedure, can state the findings, and the app, powered by NLP technology, will automatically record the results. Likewise, physicians and nurses use NLP technology to fill out a health history form of patients automatically. Such apps can also send health updates to the family of the patients.
3. NLP for Fighting Spams
Yes, NLP can be a valuable tool to monitor spam messages as well. NLP is designed to read and hear the messages. This means the NLP technology is able to read blog comments, messages, and even your private messages on social media platforms. So, NLP can easily compare to identify spam. This application is widely used in mobile apps which continually face spam issues.
4. NLP for sentiment analysis
NLP applies sentiment analysis to analyze the subtle nuances in emotions so as to determine whether they are positive or negative.
When sentiments are analyzed in real-time, one can monitor mentions on social media and take care of negative comments beforehand and also gauge customer reactions to latest marketing campaigns. This will help you have an overall idea of how customers feel about your business.
Further, you can perform sentiment analysis from time to time to understand customer likes and dislikes.
As mentioned, the uses of natural language processing are umpteen. Several app development teams out there are putting their best efforts to create apps that work in tune with NLP technology.
Today, mobile app developers are experimenting with NLP and artificial intelligence, virtual reality, and augmented reality in different industries.