How Natural Language Processing Makes Mobile Apps Smarter?

 Today it's all about text and voice data. It can be a news feed, social media posts, the free text format on web pages, and emails. To derive meaning from this data, many systems have created additional functions with our language. These systems are based on Natural Language Processing in AI (NLP), combining computational linguistics and AI. The best examples of NLP are Siri from Apple, Cortana from Microsoft, and Ok, Google from Google. This specifies the ability of NLP-based mobile devices to understand human language.

What is Natural Language Processing?

The development of new technologies (artificial intelligence and machine learning) has meant that machines can analyze and process the large amount of data provided in a short space of time. Some AI technologies even help systems learn on their own and "think" similarly to the human brain. To some extent, apps like Siri and smartphone text autocorrect have this capability. All of these solutions use Natural Language Processing technology.

The field of artificial intelligence known as "natural language processing," or NLP, integrates interactions between a computer and human (natural) language. Natural language processing makes it feasible for computers to automate, translate, or produce content that appears to be written in natural language by using machine learning to read, interpret, and decipher human languages in meaningful ways.

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Basics of Natural Language Processing

If you want to understand how natural language processing works in the most basic way, this is what happens in the interaction between a human and a machine when it comes to NLP:

• A human communicates with the machine by speaking or even using text.
  The machine receives the communication by capturing the audio or receiving the texts that the human enters.

• The computer converts the audio to text so that it can decipher and analyze what the human said.

• After that, the machine would now process the meaning of such words and the context in which they were used.

• After language processing, the machine would convert the data it processed back into audio or text.

• The machine ultimately responds to the human using the same language used in the audio or text. The information that the human entered when interacting with the device.

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Let's look at various types of mobile apps using NLP technology in different industries.

1. Using NLP to Drive an Information Engine

According to the researchers, Google will soon adapt to NLP-based technology on mobile devices to deliver better results. In addition to this, currently, virtual assistants are the best to give a basic answer to a simple question. At some point, you will start with detailed explanations of the user's complicated questions.

2. Using NLP to Combat Spam

People are facing a problem with a large number of spam messages arriving every day in their inboxes. NLP can be a useful technology when it comes to monitoring spam messages. It is a technology that reads and listens to messages. This capability of NLP technology can read the content of blog comments, email messages, private messages on social media platforms, and more. The content is then compared to known spam messages to identify spam. This natural language processing app is growing on mobile apps that have the potential to lead to spam issues.

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3. It Helps to Get to Know Your Customers Better

As a business owner, your main concern is the sentiment of your customers towards your brand. However, despite social listening, you can't judge what they feel. That's where NLP helps.

You can use it to analyze the user's feelings, thoughts, and perceptions. You can use this to build your strategies and improve acquisitions. This will help you plan the user experience and interface design to meet the needs and feelings of the user.

4. Use of NLP for Mobile Apps in the Medical Field 

NLP is frequently employed in the medical industry, particularly when developing apps for wearable medical technology. NLP also allows applications that let you speak input instead of typing. The uses for NLP in the healthcare industry are listed below:

Verbal Updates & Input: By just utilizing an app while speaking with patients, doctors and nurses can use NLP technology to automatically fill out a health history form. Similar to how a surgeon can vocally report findings while performing surgery. The family of the sufferer can also receive health updates using this kind of smartphone app.

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Does Your Company Need an NLP Application?

In this article, we talk about natural language processing, its tasks, benefits, and challenges. But how do you know if you need an NLP app for better business performance and quality results? We can conclude that NLP is good for growing companies. If you're constantly growing and it's hard for your employees to manage data manually, consider building an NLP app. If you need a comprehensive solution to get better results in targeted advertising, NLP algorithms can also help.

If you don't plan to build an application from scratch, consider integrating the NLP algorithm into your out-of-the-box solution. In case you need help with machine learning development or are looking for some expert ML advice, the Forbytes team is waiting for your ping.

How can USM help you with the best NLP solutions?

USM Business Systems has an expert team of artificial intelligence development companies in Frisco to design intelligent solutions, automate business tasks, and better serve its customers. Our expertise ranges from data capture and processing to analytics and machine learning solutions, delivering only the best for your business. Let us transform the capabilities of your business through our services. Connect with us!