Other Projects
There are numerous student-led and experimental projects in sign language translation that, while generating huge PR, face significant usability challenges in real-world applications. Here, we try to list a few of them, to provide more context on how these projects don't solve sign language translation.
SignAloud: Glove Translation Projects
MIT students have developed a glove-based solution that translates sign language into text or speech. This prototype uses sensors to detect hand movements and gestures in real-time. It won accolades like the $10,000 Lemelson-MIT Student Prize and generated impressive media attention.
However, sign language is a complex language with a rich grammar and syntax that cannot be accurately captured by simple hand gestures alone. Deaf people do not find these solutions practical for everyday use, and urge against investing in such projects[1].
Vision Pro Sign Language Translator[2]
Leveraging Apple Vision Pro’s cutting-edge hand tracking, this project promises real-time sign language translation. Although it has generated significant buzz for its potential to transform communication for deaf users, the current iteration suffers from inconsistent gesture recognition, focus only on one hand, and static gestures, making it more of a high-PR proof-of-concept than a viable everyday tool.
SpellRing: A Novel ASL Fingerspelling Translator
SpellRing is a recent wearable from Cornell University that translates ASL fingerspelling into text using micro-sonar and deep learning. Trained on over 20,000 words with an accuracy of 82–92%, it remains limited to spelling, bypassing the full spectrum of ASL’s signs, expressive grammar and non-manual cues[3].
The Atlantic. 2017. Why Sign-Language Gloves Don't Help Deaf People ↩︎
Frame60. 2025. Sign Language Translator on Vision Pro. ↩︎
Popular Science. 2025. Wearable ring translates sign language into text ↩︎