Sign language recognition method based on deep learning

School of Mathematics and Statistics, Xuzhou University of Technology, 221000, Xuzhou, China

Abstract

Sign language recognition, as an interdisciplinary field involving computer vision, pattern recognition, and natural language processing, holds profound research significance and extensive application value. This technology not only helps people with hearing impairments and those with normal hearing achieve barrier-free communication, but it also enhances their daily living experience while driving the development of sciences such as computer vision and artificial intelligence technologies. The subsequent text offers a thorough examination of the technologies involved in sign language recognition. It starts by detailing the methods for gathering data in sign language recognition, giving particular attention to hand modeling and the techniques used for visual feature extraction. Then, it discusses in detail the two methods of sign language recognition, namely traditional methods and artificial intelligence methods. These two methods have their advantages and disadvantages, providing different ideas for developing sign language recognition technology. Finally, the article proposes a prospect for the future development of sign language recognition technology, hoping that it can play a significant role in more fields and create a more convenient and barrier-free communication environment for people with hearing impairments.