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arXiv Computer Vision By Abir Bin Yousuf, Muhammad Iqbal Hossain

BDSLI: A hybrid CNN-Transformer model for Bengali Sign Language interpretation

Read the original on arXiv Computer Vision →

The paper presents BDSLI, a hybrid CNN‑Transformer architecture designed for Bengali Sign Language Recognition (SLR). It introduces a new model combination for Bengali SLR, trained on a custom video dataset of 62 sign words (250 samples per class) and evaluated against baseline models. The hybrid model achieved high accuracy—99.58% training, 99.48% validation, and 98.65% test—before being deployed in a web application for real‑world testing.

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