Sign Transition Modeling and a Scalable Solution to Continuous Sign Language Recognition for Real-World Applications
Kehuang Li, Zhengyu Zhou, Chin-Hui Lee · 2016 · ACM Transactions on Accessible Computing
This paper presents a scalable framework for continuous sign language recognition (SLR) designed to work in real-world conditions using affordable hardware. The researchers address a fundamental challenge in SLR: modeling the transitions between signs. Unlike spoken language…
sign language recognition · hidden Markov models · machine learning · deaf and hard of hearing · wearable technology