2013/04/11 by Maher Jebali, Jebali, Maher, Patrice Dalle +3
Computer Science · Psychology · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Gaze Tracking and Assistive Technology #Hand Gesture Recognition Systems #Hearing Impairment and Communication #cs.CL
paper · pdf · doi:10.48550/arxiv.1304.3265
arxiv created 2013/04/11 · openalex publication_date 2013/04/11 · arxiv updated 2013/04/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Computers still have a long way to go before they can interact with users in a truly natural fashion. From a users perspective, the most natural way to interact with a computer would be through a speech and gesture interface. Although speech recognition has made significant advances in the past ten years, gesture recognition has been lagging behind. Sign Languages (SL) are the most accomplished forms of gestural communication. Therefore, their automatic analysis is a real challenge, which is interestingly implied to their lexical and syntactic organization levels. Statements dealing with sign language occupy a significant interest in the Automatic Natural Language Processing (ANLP) domain. In this work, we are dealing with sign language recognition, in particular of French Sign Language (FSL). FSL has its own specificities, such as the simultaneity of several parameters, the important role of the facial expression or movement and the use of space for the proper utterance organization. Unlike speech recognition, Frensh sign language (FSL) events occur both sequentially and simultaneously. Thus, the computational processing of FSL is too complex than the spoken languages. We present a novel approach based on HMM to reduce the recognition complexity.