The mobile sector is booming with a large number of apps being created every day. As a result, there has been a race to make the best mobile apps accessible to all users across different devices. Implementing AI for mobile app accessibility has become a huge part of the process. These tools can be used by app developers and website developers alike to make sure that people with physical impairments can still enjoy the benefits of today’s state-of-the-art applications.
What Is Mobile App Accessibility?
Mobile app accessibility focuses on a user’s ability to obtain, use and take full advantage of a mobile application or device. There are a number of impairments that prevent mobile apps from being accessible to everyone. Some common ones are:
- Vision: Users with low vision have difficulty seeing text or images clearly or distinguishing certain colors on a screen. Vision impairments are some of the most common ones.
- Hearing: Users with hearing impairment have difficulty hearing the audio attached to a mobile app. This is another very common one.
- Mobility: These impairments make it difficult for users to swipe, press buttons or interact with the app in any way. This includes people who cannot lift their hands or move their fingers.
- Speech: Users who are speech impaired have difficulty understanding the text on the screen.
While there are many more impairments that make it harder for people to access and handle mobile apps, the goal is to remedy this, placing today’s technology within reach of all users without having to make any changes in the code for its original design.
How Can AI Increase App Accessibility
There are many AI tools available today that can assist with mobile app accessibility including:
Text-To-Speech (TTS): This tool reads out the text on the screen. It can be used for apps where a user needs to select buttons and other elements by placing an icon or cursor over it. The TTS will then read out that element making it easier for people with vision impairments to use the app effectively.
Text-To-Braille (T2B): This is a system where a user can attach text to a display and have it read out in Braille. There are many benefits for blind users including being able to read documents, books, labels and notes without needing to rely on someone else’s assistance.
Voice-Activated Controls: These tools allow people with limited mobility or disabilities that affect fine finger movements to use their voice to interact with the phone.
Gesture Control: This tool allows users to use hand movements and gestures to control various functions on their mobile phones instead of using touch screens. For example, a user can open a navigation panel by tracing out a certain shape with their finger in the air or move around an image by drawing a circle on the screen.
AI Assistants in Action
There are many mobile apps that have already integrated AI with accessibility features for users with disabilities. Here are just a few examples:
Voice Dream Reader is an iOS app that has Voice-Activated Controls which lets readers use their voice to navigate through documents and read them out loud. It supports many different file formats and is designed with students in mind.
MySMS gives users the ability to attach text directly to the screen of their mobile phone with Text-To-Braille which then reads out that information via a Braillenote connected to the MySMS device. The app also includes sticky labels for people who can’t read Braille.
All of these tools can be used by app developers and website developers alike to make sure that people with physical impairments can still enjoy the benefits of today’s state-of-the-art applications.
How Can AI Be Implemented Into Mobile Apps?
AI can be implemented into mobile apps by enabling them to understand voice commands and queries. AI is also capable of learning from human interaction which means that it will adapt to changes in circumstances, behavior, or environment over time.
There are many tools available for developing AI-enabled apps, such as:
- Google Cloud Platform, which offers a cloud machine learning platform and includes TensorFlow Lite to help with Android development
- IBM Watson, which is capable of speech-to-text and text-to-speech capabilities and provides a library for Android development called Speech to Text SDK
- Google Accessibility Suite is free for Android devices with text-to-speech capabilities.
How Has Machine Learning Implemented AI?
Deep learning is a powerful process supervised by humans. It uses neural networks, pattern recognition and disciplines including computer vision, natural language processing (NLP), and speech recognition to build apps that are capable of identifying patterns.
A common application of machine learning is image classification, where the software is given known examples of images with certain features which can include text labels and shapes. The software must be able to learn what differentiates each image, and then apply that knowledge when presented with new images that it has not yet seen before.
Another example is handwriting recognition which uses machine learning. Before computers can read handwritten text they need to be taught how to recognize letters and numbers in cursive form. This process begins by converting handwritten text into digital images and then analyzing the image to find the most likely matching character.
Machine learning is also used in photo apps such as Prisma which can transform a normal picture into an impressionist painting using AI. It does this by breaking down the style of other famous artists like Van Gogh, Picasso, and Mondrian and replicating it in a new image.
Machine learning is also used to add context to conversations. An app called SwiftKey for example helps people communicate better on messaging platforms by predicting responses to messages, making communication faster and more accurate. It uses machine learning to improve its natural language processing capabilities and provides a more personalized experience each time a user uses the app.
AI is a powerful tool for developers to improve the user experience of mobile apps by making them more accessible for all users including those with disabilities. We’ve seen that many tools exist for developing AI-enabled apps, paving the way for a future in which developers have access to powerful technologies to create apps with extraordinary features that ordinary people can use.
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