- Inspiration
- Introduction
- How It Works
- Features
- Tech Stack
- Working Demo
- Contributors
- Team readmore.ai
readmore.ai is inspired by the staggering number of individuals worldwide diagnosed with learning disabilities, accounting for approximately 15% of the global population. Additionally, it aims to cater to those with ADHD and short attention spans. It is also an incredibly useful tool for providing kids and toddlers with an interesting reading experience. The idea is to develop a solution that not only enhances the reading experience but also makes it more accessible and engaging for everyone.
readmore.ai is a groundbreaking app designed to revolutionize the reading experience by integrating AI-generated Context-Aware Visuals and Audio. Through advanced AI technologies, the app aims to provide users with an extra incentive to engage with reading material, making it more enjoyable and immersive.
The app's core functionality revolves around enhancing the reading experience with AI-generated visuals and audio. Here's a breakdown of its operation:
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User Authentication:
- Users can sign up or log in to access the app's features securely.
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Book Selection:
- Upon logging in, users can explore a curated selection of books available within the app's library.
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Reader View:
- After selecting a book, users are directed to a reader view, where they can delve into the content paragraph by paragraph.
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AI Integration:
- When a user selects a paragraph, a POST request is sent to the Flask backend, leveraging the GPT-3.5 API to generate prompts for both image and audio models.
- These prompts are then utilized to generate context-aware visuals and audio corresponding to the selected paragraph using AI models such as "dreamlike light" for images and "musicgen" for audio.
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Rendering Content:
- The generated visuals and audio are asynchronously rendered in the app, enhancing the reading experience and providing users with a multi-sensory engagement.
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Consistency with Seeding:
- To ensure consistency within the generated content for the same story, seeding techniques are implemented, providing users with a cohesive reading experience.
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Enhanced Reading Experience: AI-generated visuals and audio complement the reading material, enriching the user experience and fostering engagement.
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Multi-Sensory Engagement: Users can experience reading through a combination of visually stunning imagery and immersive audio, creating a multi-sensory engagement that enhances comprehension and enjoyment.
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Personalized Content: Leveraging AI models, the app delivers context-aware content tailored to each paragraph, ensuring a personalized reading experience for every user.
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Frontend: Flutter - An open-source cross-platform UI framework for building responsive and captivating user interfaces.
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Backend: Flask - A lightweight Python web framework ideal for handling HTTP requests and seamlessly integrating with AI models.
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AI Models: GPT-3.5 - A state-of-the-art language model used for generating prompts for both image and audio models, enabling context-aware content generation.
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Image Generation: "dreamlike light" - An AI model specialized in generating visually captivating imagery based on text prompts.
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Audio Generation: "musicgen" - An AI model designed to produce immersive audio experiences tailored to text prompts.
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- GitHub: Siddhant Jagdish
- GitHub: Shubh Kanodia
- GitHub: Sowmesh Sharma
- GitHub: Shubham Kanekal