Isharah: A Large-Scale Multi-Scene Dataset for Continuous Sign Language Recognition

Current benchmarks for sign language recognition (SLR) focus mainly on isolated SLR, while there are limited datasets for continuous SLR (CSLR), which recognizes sequences of signs in a video. Additionally, existing CSLR datasets are collected in controlled settings, which restricts their effectiveness in building robust real-world CSLR systems. To address these limitations, we present Isharah, a large multi-scene dataset for CSLR. It is the first dataset of its type and size, collected in an unconstrained environment using signers' smartphones. This setup resulted in high variations of recording settings, camera distances, angles, and resolutions. This variation helps with developing sign language…