Think about this: millions of people in India speak Hindi or Bengali as their primary language, yet almost all online image descriptions (alt-text) are in English only.
This creates a massive barrier for visually impaired users. Screen readers can't help if they can't speak the language!
The current solutions were slow (manual translation) or inadequate (existing tools struggle with Indic scripts). This was a problem begging for a modern, accessible solution.
My AI-Powered Solution: Project A.I.D.
I built Project A.I.D. (Accessible Image Descriptions) to fix this, using a lean, modern tech stack:
📸 Analyze: A user uploads an image. We use a Vision-Language Model (BLIP from Hugging Face) to generate a detailed English description in seconds.
🌐 Translate: We instantly pipe that description through the Google Translate API into high-quality Hindi (हिंदी) and Bengali (বাংলা).
🔊 Speak: The Web Speech API provides immediate text-to-speech in all three languages.
This is all running on a Python/Flask backend and built on a $0 budget—proving that impact doesn't require massive resources.
Why This Matters
This project isn't about solving a small tech issue; it's about giving full digital access and dignity to millions of people who are currently excluded. I taught myself to code specifically to build solutions that matter, and I believe this is one of them.
Impact: Directly supports accessibility for hundreds of millions of people.
Tech: Leverages powerful open-source AI (Hugging Face Transformers).
Access: Simple, clean, multilingual interface.
Let's Talk Civic Tech: The Future of Multilingual AI
I'm focused on social-impact projects—from this accessibility tool to my real-time fact-checker, Veritas.
I'm looking for community feedback:
What's the best way to get this tool into the hands of NGOs and non-profits in India?
Are there any other high-impact, low-cost AI models you'd recommend integrating for other Indian languages?
Let me know your thoughts!
https://github.com/shalinibhavi525-sudo/A.I.D
Top comments (0)