Inspiration
Students struggle with reading research papers and articles due to issues with knowledge comprehension, material retention, and difficulty staying on track with dense material. We wanted to improve efficiency by integrating an ai-powered reading comprehension tool into the workspace.
What it does
PagePal effortlessly transitions between article sections and is able to provide explanations and summaries for difficult paragraphs. It also identifies if the user is distracted and draws them back into the reading, as well as generates practice questions on command to improve reading comprehension. All of these features are prompted by simple visual cues.
How we built it
We built our tool using React, AWS, Javascript, and Python.
Challenges we ran into
A lot of the gestures we initially planned on using proved too difficult for the camera to recognize. As such, we had to simplify the visual cues in order for the tool to work as seamlessly as possible.
Accomplishments that we're proud of
We are proud of the clean and simple UI, which makes it really simple for users to get acquainted with our tool.
What we learned
We gained experience working with computer vision and gesture recognition models.
What's next for PagePal
In the future, we want to personalize reading speed in order to have a more accurate baseline for each user. We also want to track eye movement in order to more accurately determine distraction level. Additionally, we hope the tool will be able to offer suggestions such as break times based on declining reading speed and visual fatigue cues. Lastly, we hope to create a Chrome extension in addition to the app.
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