Generation and Detection of Sign Language Deepfakes – A Linguistic and Visual Analysis
Shahzeb Nacem, Muhammad Riyyan Khan, Usman Tariq, Abhinav Dhall, Carlos Ivan Colon, Hasan Al-Nashash
2024
Generation, Discernment, Detection, Dataset, Accessibility, American Sign Language
This research presents a positive application of deepfake technology in upper body generation, while performing sign-language for the Deaf and Hard of Hearing (DHoH) community.
Systemic Biases in Sign Language AI Research: A Deaf-Led Call to Reevaluate Research Agendas
Aashaka Desai, Maartje De Meulder, Julie A. Hochgesang, Annemarie Kocab, and Alex X. Lu
2024
Accessibility, American Sign Language
This study conducts a systematic review of 101 recent papers in sign language AI. The analysis identifies significant biases in the current state of sign language AI research, including an overfocus on addressing perceived communication barriers, a lack of use of representative datasets, use of annotations lacking linguistic foundations, and development of methods that build on flawed models.