sign-language

This paper introduces the eJSL Dialog dataset for emotion recognition in sign language conversations, addressing the lack of conversational context in existing datasets. Benchmarking shows a domain gap when applying generic multimodal models, highlighting the need for context-aware visual extractors for sign language.

This paper introduces a direct sign-to-sign translation model that bypasses intermediate text by using back-translation to create synthetic parallel sign language data, achieving significant improvements in speed and accuracy over cascade methods for ASL, CSL, and DGS.

A research paper presenting a dataset and XGBoost-based model for sentiment analysis of German Sign Language (DGS) fairy tales using facial and body motion features extracted via MediaPipe, achieving 63.1% balanced accuracy and demonstrating the importance of both facial and body movements for sentiment communication in sign language.

Ona AI is building digital sign language avatars and inclusive datasets to improve accessibility for deaf and hard of hearing communities.

Ona AI is developing digital sign language avatars and inclusive datasets to create assistive technology for learners with hearing impairments.