FOR IMMEDIATE RELEASE

Enseñas: Machine Learning Model for Real-Time Mexican Sign Language Translation

Eduardo Guizar Vukovich introduces Enseñas, a digital platform aimed at improving communication for the hearing impaired in Mexico. The lack of education and tools for Mexican Sign Language has led to the creation of a machine learning model that enables real-time translation, bridging the communication gap between individuals with hearing disabilities and those without. This innovative tool aims to promote inclusion and accessibility.

Developed over a 6-month period at Universidad de Monterrey and in Monterrey City, Mexico, the Enseñas project addresses the limited resources and tools available for the hearing impaired in Mexico. Through extensive research and interviews with experts, the team identified the need for a solution to facilitate communication and improve the independence of individuals with hearing disabilities.

The project's unique approach involves the creation of a machine learning model, the LSM Model, which can translate Mexican Sign Language into written Spanish and vice versa in real time. By leveraging technology and current tools, the platform aims to make the lives of individuals with hearing disabilities easier and more inclusive.

One of the key challenges overcome in the development of Enseñas was the creation of a comprehensive data set consisting of 400 videos of the most commonly used words in Mexican Sign Language. This data set was then used to train the machine learning model to accurately recognize and translate signs in real time.

Enseñas is not just a tool for real-time translation; it is also a platform for sharing knowledge and resources. The project's digital platform allows for the free download of the LSM recognition model and the data set, enabling other developers, technology companies, and educational institutions to leverage the project and create more inclusion tools for the non-hearing community.

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