Building Handly: Researching AI-Assisted Indian Sign Language Recognition for Real-Time Communication
Exploring the research behind Handly, an AI-assisted video communication platform designed to bridge the communication gap between deaf and hearing individuals through real-time Indian Sign Language recognition.
Building Handly: Research Before Implementation
Handly is an AI-assisted video communication platform that explores how Indian Sign Language (ISL) recognition can be integrated into real-time video calls. Instead of jumping straight into development, the current focus is understanding the problem, studying existing research, and evaluating what is technically feasible.
Research in Progress Handly is currently in the research and exploration phase, focusing on the feasibility of integrating AI-assisted Indian Sign Language recognition into real-time video communication while acknowledging the challenges of continuous ISL translation.
Why Handly?
Communication technology has advanced rapidly, but accessibility still has room to improve. Most video calling platforms don't provide built-in support for Indian Sign Language, making communication more difficult for many deaf users.
- Existing video communication platforms do not support native Indian Sign Language recognition.
- Deaf users often rely on interpreters or text-based communication during online conversations.
- AI has the potential to make communication more accessible and inclusive.
Research Challenges
One of the biggest discoveries so far is that sign language recognition is far more complex than simple gesture detection.
- Continuous sign language recognition is significantly harder than recognizing isolated signs.
- Facial expressions, body posture, and temporal context all contribute to meaning.
- Limited publicly available ISL datasets remain a major challenge for research and development.
Current Progress
The project is currently focused on research and experimentation before moving into full-scale implementation.
- Reviewing recent research papers on Indian Sign Language recognition.
- Evaluating publicly available datasets and benchmark models.
- Exploring deep learning architectures suitable for real-time inference.
Proposed Direction
The long-term goal is to build an AI-assisted communication platform that enables accessible one-to-one video conversations through live caption generation.
- Flutter for the cross-platform mobile application.
- WebRTC for low-latency real-time video communication.
- FastAPI, Firebase, and PyTorch for backend services and AI integration.
Looking Ahead
There's still a long way to go, but every experiment helps answer an important question: can AI make communication more accessible without disrupting the natural flow of conversation?
- Continue validating research findings through experimentation.
- Develop and evaluate an initial working prototype.
- Share progress, challenges, and lessons learned throughout the journey.
Final Thoughts
Handly is more than just another development project. It's an opportunity to explore how AI can contribute to more inclusive communication. While the road ahead involves plenty of research and experimentation, I'm excited to continue building, learning, and sharing the journey.
- Accessibility remains the core motivation behind the project.
- Research is guiding every technical decision.
- Future updates will document the project's progress and key learnings.