OpenHands: Making Sign Language Recognition Accessible with Pose-based Pretrained Models across Languages

Understand

AI technologies for Natural Languages have made tremendous progress recently.

• However, commensurate progress has not been made on Sign Languages, in particular, in recognizing signs as individual words or as complete sentences.
• We introduce OpenHands, a library where we take four key ideas from the NLP community for low-resource languages and apply them to sign languages for word-level recognition.
• First, we propose using pose extracted through pretrained models as the standard modality of data to reduce training time and enable efficient inference, and we release standardized pose datasets for 6 different sign languages - American, Argentinian, Chinese, Greek, Indian, and Turkish.