Challenges for Linguistically-Driven Computer-Based Sign Recognition from Continuous Signing for American Sign Language
This work addresses the problem of continuous sign recognition for ASL users, but it is incremental as it focuses on outlining challenges rather than presenting new solutions.
The paper identifies challenges in computer-based recognition of signs from continuous signing in American Sign Language, based on a large annotated corpus, and discusses linguistic regularities that could improve handshape and sign recognition.
There have been recent advances in computer-based recognition of isolated, citation-form signs from video. There are many challenges for such a task, not least the naturally occurring inter- and intra- signer synchronic variation in sign production, including sociolinguistic variation in the realization of certain signs. However, there are several significant factors that make recognition of signs from continuous signing an even more difficult problem. This article presents an overview of such challenges, based in part on findings from a large corpus of linguistically annotated video data for American Sign Language (ASL). Some linguistic regularities in the structure of signs that can boost handshape and sign recognition are also discussed.