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AI / Computer Vision

Real-Time Indian Sign Language Recognition

Developed a comprehensive real-time Indian Sign Language recognition system using YOLO and YOLO-NAS architectures. The system supports both single and multi-person gesture recognition with sentence-level understanding. Integrated MediaPipe for skeletal keypoint extraction, significantly enhancing gesture accuracy.

YOLO-NASMediaPipePythonTensorFlowOpenCVNLPLSTM
GitHub Repository
IEEE ICONAT 2024
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The Problem

Deaf and hard-of-hearing individuals face significant communication barriers. Existing sign language recognition systems lack real-time capability and multi-person support.

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The Solution

Built a bidirectional translation system between text, voice, and ISL using deep learning and NLP, achieving 15% improved accuracy and 75ms reduced latency.

// OUTCOMES

Key Results

15% increase in sign recognition accuracy
75ms reduction in translation latency
Support for multi-person gesture recognition
Sentence-level sign language understanding