Bridging communication with machine learning in sign language recognition for Vietnamese

Abstract

Vietnamese Sign Language (VSL) serves as the primary language for deaf and hard-of-hearing individuals in Vietnam. This paper explores the sign language recognition process for VSL, emphasizing the role of machine learning in bridging communication barriers. We delve into the basics of VSL, detailing the one-to-one correspondence between hand signs and Vietnamese alphabet letters and address the formation of words through sequential hand signals and diacritics placement. Furthermore, the paper highlights the importance of pausing between words and the utilization of machine learning algorithms for automated sign recognition. Lastly, we conclude by discussing the potential applications and future directions of VSL recognition technology in Vietnam.