Machine Learning
Bangla Sign Language Translator
This real-time translation web application bridges communication barriers for the Bangla-speaking deaf and hard-of-hearing community. The system utilizes optimized deep learning models to recognize 10 Bangla digits and 35 Bangla sign characters with high accuracy. Built with data augmentation handling (expanding a core 9,000 image dataset up to 36,000 samples), it incorporates models tested against MobileNetV2, ResNet, and CustomCNN structures. Additional modules include live verification feedback loops alongside an integrated learning hub featuring curated tutorial playlists.
Project overview
A Flask-based web application that translates Bangla sign language characters and digits into written Bangla in real-time to promote inclusive communication. This project reflects my interest in combining practical implementation with clear user value, whether through interface design, backend structure, or research-driven experimentation.