Ensenas Amrazê Peywendiyê by Saeli Seira Saenz and Alana Betanzo Carriles

Ensenas Amrazê Peywendiyê by Saeli Seira Saenz and Alana Betanzo Carriles is a highly esteemed winner of the very prestigious 2023 Xelata A' Design Award a Hesinîn in Dîzayna Civakî Competition Category.

HesinCivakî· 2023

Ensenas Amrazê Peywendiyê

by Saeli Seira Saenz and Alana Betanzo Carriles

Client: Universidad de Monterrey

Xelata A' Design Award a Hesinîn Winner in Civakî Category

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The Design

About Ensenas Amrazê Peywendiyê

Ensenas amrazek dîjîtal e ku hatiye afirandin da ku peywendiya di navbera kesên bi seqetiya bihîstinê û kesên bihîstok li Meksîkayê baştir bike. Ensenas modelek fêrbûna makîneyê bikar tîne ku Zimanê Îşaretê yê Meksîkî bi rengekî rasterast dixwîne û peyvan wergerîne Spanî ya nivîskî. Ev model bi komek daneyê ya ji 400 vîdeoyên îşaretên gelemperî hatiye perwerdekirin, ku her yek ji wan wek çarçove bi çarçove hatiye nîşankirin û analîzkirin bi riya texmînkirina rewşê (pose estimation). Malperek bersivdar projeyê pêşkêş dike û lêkolîn, model û komek daneyê ji bo daxistina belaş peşkêş dike. Armanc kêmkirina valahiya peywendiyê ye.

The Recognition

About the Xelata A' Design Award a Hesinîn

Ensenas Amrazê Peywendiyê xelatgirê Xelata A' Design Award a Hesinîn e, nasîneke bi prestîj ku ji sêwiranên baş re tê dayîn, yên ku pêdiviyên pîşeyî û pîşesaziyê yên ku ji afirandinên baş hatine sêwirandin têne hêvîkirin tînin cih. Xelatgirên Hesinînê jêhatîbûna mezin, pisporiya bilind, têgihiştina pisporî û kapasîteya afirîner a afirînerên xwe nîşan didin. Tê hêvîkirin ku Ensenas Amrazê Peywendiyê afirandineke pir hatiye rêzgirtin, sitayişkirin û delal, pratîkî û nûjen be. Ev sêwirana bi Hesinînê serketî pratîkên çêtirîn ên pîşesaziyê yekgirtî dike û xwedî taybetmendiyên teknîkî yên jêhatî ye ku bi zanîn û jêhatîbûnê ve girêdayî ne. Ensenas Amrazê Peywendiyê ji ber baldariya xwe tê rêzgirtin û hatiye sêwirandin da ku kalîteya jiyanê baştir bike û alîkariya çêtirkirina dinyayê bike.

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