Ensenas Zouti Kominikasyon by Saeli Seira Saenz and Alana Betanzo Carriles

Ensenas Zouti Kominikasyon by Saeli Seira Saenz and Alana Betanzo Carriles is a highly esteemed winner of the very prestigious 2023 A' Design Award Fè in Sosyal Competition Category.

FèSosyal· 2023

Ensenas Zouti Kominikasyon

by Saeli Seira Saenz and Alana Betanzo Carriles

Client: Universidad de Monterrey

A' Design Award Fè Winner in Sosyal Category

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Colors

The Design

About Ensenas Zouti Kominikasyon

Ensenas se yon zouti dijital ki kreye pou amelyore kominikasyon ant moun ki gen andikap sou tande ak moun ki tande nan Meksik. Ensenas itilize yon modèl aprantisaj machin ki li Lang Siy Meksiken an tan reyèl epi tradui mo yo an Panyòl ekri. Modèl la te antrene ak yon ansanm done ki gen 400 videyo siy komen, ki make epi analize kadav pa kadav atravè estimasyon pòz. Yon sitwèb reaktif prezante pwojè a epi ofri rechèch la, modèl la ak ansanm done a gratis pou telechaje. Objektif la se redwi eka kominikasyon an.

The Recognition

About the A' Design Award Fè

Ensenas Zouti Kominikasyon se yon ganyan A' Design Award Fè, yon rekonesans ki gen prestij yo bay bon design ki satisfè egzijans pwofesyonèl ak endistriyèl yo atann de kreyasyon ki byen fèt. Ganyan Fè yo montre gwo konpetans, espesyalizasyon wo, konpreyansyon ekspè ak kapasite kreyatif kreyatè yo. Yo atann Ensenas Zouti Kominikasyon pou se yon kreyasyon anpil moun estime, admire e renmen ki pratik e inovatè. Design sa a ki ganyen A' Design Award Fè entegre pi bon pratik sektè a e li gen karakteristik teknik konpetan ki lye ak konnesans pratik ak talan. Yo respekte Ensenas Zouti Kominikasyon pou jèntan li e li fèt pou bay amelyorasyon kalite lavi ki ede fè mond lan vin yon pi bon kote.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: Likewise, thanks to technology and current tools, we were able to generate a Machine Learning model or tool which makes a real time reading of the Mexican Sign Language; where it is possible to solve the communication gap between people with hearing disabilities and people without such disability; avoiding that people make the effort to learn the Mexican Sign Language.
Dimensions & Packaging: This is a model in a website, whit a responsive design.
Tags: IA, Machine Learning, LSM, Data base, Service Design, education and tools, Sign Language,
Production Technology: We developed a model and data set of machine learning in order to create new tools and opportunities for people with hearing disabilities and make their lives easier through it. We created a platform in which anyone can learn more about the project and download the machine learning model.
Design Challenge: The first step in creating this project was the creation of a data set consisting of a collection of 400 videos of the most used words in the Mexican sign language. These were ordered by categorize and label individually.
The next step was the pose prediction process, in which the model analyzes the content of the data set analyzing frame by frame by means of ML pipe pose Estimation.
At the end of this estimation, our supervised learning model is able to detect patterns in the poses without the need for human intervention in order to identify which words, letters, numbers and phrases they belong to. To complete this process, a manual selection of frames was also performed in order to achieve a more accurate prediction of the signals.

In order to open this project to the public, a digital platform was created in which it is possible to freely download our research, the LSM recognition model, the data set generated so that other developers, technology companies, educational institutions can take advantage of our project and can create more inclusion tools for the non-hearing community.
Research: It is estimated that 5% of the world population, being 430 million people, will suffer a loss of disabling audio and in Mexico there are limited resources and tools to create an environment where everyone feels heard.
Following a design process, we conducted a series of interviews with experts, case studies and surveys to understand the perception of hearing impairment. We found that one of the limitations for the use of sign language is the learning curve.

We also found that some basic tasks for people with this disability can be more complicated than normal, which limits their independence. That's why we wanted to find a solution
inclusion to this problem.

This is Enseñas, an initiative that seeks inclusion through a digital tool made by through a machine learning model (LSM Model) with the purpose of creating a new way of
communication that facilitates the interaction between people with hearing disabilities and hearing people in real times. This model will be able to translate words from the Mexican sign language into Spanish written and vice versa in real time.
Inspiration: The lack of education and tools about Mexican Sign Language to improve the communication and experience of hearing impaired people in Mexico, has led us to create awareness and promote the inclusion of this problem through a digital platform.
Project Duration: 6 months on Universidad de Montery and Monterrey City in México
Team Members: Saeli Seira Sáenz
Alana Betanzo Carriles