Development of a Mobile Application with Artificial Intelligence for Mexican Sign Language Recognition

Bogart Yail Marquez; Arnulfo Alanis; Angeles Quezada; José Sergio Magdaleno-Palencia

doi:10.3991/ijim.v19i09.54205

Authors

Bogart Yail Marquez Tecnológico Nacional de México, Campus Tijuana, Tijuana, Baja California, México https://orcid.org/0000-0001-7334-374X
Arnulfo Alanis Tecnológico Nacional de México, Campus Tijuana, Tijuana, Baja California, México https://orcid.org/0000-0003-2481-8563
Angeles Quezada Tecnológico Nacional de México, Campus Tijuana, Tijuana, Baja California, México https://orcid.org/0000-0001-5706-8047
José Sergio Magdaleno-Palencia Tecnológico Nacional de México, Campus Tijuana, Tijuana, Baja California, México https://orcid.org/0000-0001-5832-2473

DOI:

https://doi.org/10.3991/ijim.v19i09.54205

Keywords:

Mexican Sign Language, AI (Artificial Intelligence), Machine Learning,, Image Processing, educational inclusion

Abstract

In Mexico, the community of people with hearing disabilities faces significant communication barriers due to the limited availability of interpreters and the lack of supportive technological tools. This paper presents the development of a sign language system using artificial intelligence (SLSAI), a mobile application that uses artificial intelligence (AI) for the recognition of Mexican sign language (MSL). Using machine learning techniques and image processing, SLSAI translates signs from the alphabet in real-time, facilitating interaction between deaf and hearing individuals. Additionally, the tool features a module where students can learn sign language through interactive games, creating a fun and engaging learning environment. The development methods, obtained results, and social implications of the tool are discussed.