How Natural Language Processing Makes Mobile Apps Smarter?
How Natural Language Processing Makes Mobile Apps Smarter?
Natural Language Processing (NLP) technology is one of the hottest topics in the mobile app development industry. Organizations are more interested to integrate NLP capabilities in mobile applications and offering their customers more convenient and optimized access to app features.
Siri is the best example of NLP-based Artificial Intelligence (AI) application. It will be activated and respond to user commands with simple voice commands. For instance, if the user asks “Hey Siri, what’s the weather today?”, this app gives the most precise information related to today’s weather. It is all because of its built-in Natural Language Processing (NLP) and speech recognition capabilities.
Driven by the intelligent collaborative features of NLP technology, enterprises are focusing on integrating NLP into their mobile apps.
In this article, we walk you through how NLP technology makes mobile apps smarter and more efficient. Being the best mobile app development company, we also help you know the estimated costs of AI apps development using NLP.
What Is Natural Language Processing?
NLP is a stream of Artificial Intelligence (AI). By using machine learning abilities, NLP plays a vital role in processing and understanding human spoken language.
So, NLP technology makes mobile applications or computer devices to listen to user queries, convert them into machine understandable text, interpret it, and interact with humans in their native language.
Here are the best examples of NLP mobile apps:
- Personal assistant apps like Amazon Alexa
- Apple’s Siri like voice assistant app
- Google Translate
- Mobile GPS navigation apps
- Mobile healthcare apps
- Market intelligence apps
- Customer sentiment tracking apps
- Virtual customer support apps
How To Use NLP in Mobile Apps?
Natural Language Processing technology is increasingly used in mobile apps to automatically analyze human voice commands and give appropriate responses for improving their app experience. Such intelligent and automatic responses from applications improve customer services and brand credibility. Here are a few best applications of NLP in real-time.
Uses Of NLP Technology in Mobile App Development
- NLP in mobile healthcare apps development
NLP technology has become a core technology for healthcare apps development for Android, iOS, and wearables. The medical and healthcare sector to offer hands-free communication services to their audience is embracing NLP technology and creating flourishing apps. Here are a few significant applications of NLP integration in healthcare apps.
For taking notes automatically: While consulting a physician online, NLP apps help patients in automatically deriving useful information such as healthcare tips, medications, dosages, etc., from the doctor’s speech.
For controlling medical devices: It is one of the best advantages of using NLP in the medical field. Integration of NLP in medical devices could help physically disabled people to well interact with their gadgets or any other devices with their voices.
Recommend to Read: 10 Best Artificial Intelligence Powered Healthcare Mobile Apps in 2021
- Use of NLP in GPS navigation applications
Natural Language Processing technology is also widely adopted by organizations for developing location finding apps. NLP apps will allow users to ask for directions to reach their destinations without hassle.
Google Assistant is the best example for navigating to a place. With simple voice commands like Ok Google or tapping the microphone symbol, users can find locations and get things done while driving. Thanks to advancements in mobile technologies.
Using NLP-powered Google Assistant, users make hands-free calls, messages and even play music on the go. Further, users can also find nearby places and get directions through the shortest traffic-free routes. The one thing that the user has to do is focus on driving, and the rest of the things will take care by the intelligent NLP apps.
- NLP for language translation in apps
Google Translate is the best instance for this application. Yes. Leveraging the power of speech recognition technology, Google translate app can detect a language and translate it into another language as per the user requirement with 100% accuracy.
Voice recognition technology has replaced various input methods like typing and selecting options. Users can tap on the microphone and start a conversation with NLP apps to meet their needs.
USM Business Systems, one of the best AI apps development company (USA), help companies create intelligent AI Android apps like Google Assistant and gear them towards success in this competitive digital world.
- NLP Technology for Spam Monitoring
NLP technology is not limited to just understanding user languages, but it is also best for deriving text patterns, reading content, and identifying spam mails in a fraction of a second.
Google is using NLP to monitor spam content. NLP tools or apps will read information across various social media platforms, websites, and emails to analyze the most common words, idioms, and sentences and filter out spam content. This application for NLP is increasingly used in mobile apps to address a solution for spam-related issues.
- Use of NLP For Analyzing Customer Sentiments online/offline
Customers are revenues sources for any business. Until and unless achieving customer satisfaction, a business cannot create brand value in the market. AI and NLP mobile apps help companies in analyzing the sentiments from customer feedback and reviews about their products or services on social platforms.
NLP-based applications, using ML and AI technologies, can search for negative feedback across mediums and assist businesses in optimizing their service or product qualities as per the user requirements.
It means sentiment analysis helps organizations to check whether customers are satisfied with their products or services.
How Much Does It Cost To Develop AI Mobile Apps For Android/iOS With NLP?
USM, the best mobile app development service provider with vast experience in the app development field, confidently says that native iPhone/Android apps development using NLP capabilities is a profitable and long-term decision.
As we discussed in many of our mobile app development articles, the cost of Android apps or iPhone apps depends on various factors. Along with features, functionalities, platform, app type, application developer’s location, app size, and all, the cost factor drastically varies based on the technologies you choose.
Of course, the cost will go high if you need a mobile app that is integrated with the latest digital technologies like Artificial intelligence, machine learning, natural language processing.
For instance, the development cost of a custom AI solution might range from $30,000 to $300,000 for a single platform. At USM, with our in-depth knowledge of cutting-edge technologies, we help you develop a budget-friendly and futuristic AI solution that meets the desired needs of your business.
NLP technology in Mobile Apps development improves the communication medium between brands and end customers online. It helps organizations make their brand available 24/7 by responding to user verbal queries instantly.
Combined with AI and ML technologies, integration of NLP in mobile app development applications will ensure a bright scope in the future. The demand for NLP-infused AI apps will be expected to occupy more space in this mobile world. From virtual personal assistants, and healthcare applications to GPS navigating apps (for location tracking) and AI chatbots, every application needs NLP to facilitate the best experiences for users.
Amazon, Google, Microsoft, and Apple-like biggest tech companies are reaping the benefits from their artificial intelligence, ML, and NLP-based applications. Be the next one and invest in AI and human language processing apps development.
USM, the best AI app development company, has a core team of AI developers who have years of proven experience in creating intelligent mobile apps using the power of speech-to-text and text-to-speech technologies.