UFAZ teacher Nigar Alishzada’s paper, published in Elsevier, introduces the first-ever Azerbaijani Sign Language Dataset (AzSLD)

Nigar Alishzada, a computer science teacher at the French-Azerbaijani University (UFAZ), has co-authored a research paper in Elsevier with Jamaladdin Hasanov. Titled “AzSLD: Azerbaijani Sign Language Dataset for Fingerspelling, Word, and Sentence Translation with Baseline Software”, the paper introduces the first-ever Azerbaijani Sign Language Dataset (AzSLD).

This dataset, aimed at supporting the Deaf community in Azerbaijan, comprises 30,000 annotated videos showcasing fingerspelling, words, and sentences. The data, collected from diverse participants, was captured with dual-camera setups for enhanced visual quality.

AzSLD and its source code are freely accessible, providing a crucial resource for researchers and developers to advance sign language recognition and translation technologies.