Jern Sosial · 2023
Ensenas Kommunikasjonsverktøy
by Saeli Seira Saenz and Alana Betanzo Carriles
- A' Design Award i Jern 2023 in Sosial
- CLIENT: Universidad de Monterrey
- Estimated Number of Design Views: 34,628
- Verification code CCB43F0D2F · Verify this award
Colors
About Ensenas Kommunikasjonsverktøy
Ensenas er et digitalt verktøy skapt for å forbedre kommunikasjonen mellom personer med hørselshemming og hørende personer i Mexico. Ensenas bruker en maskinlæringsmodell som leser meksikansk tegnspråk i sanntid og oversetter ord til skriftlig spansk. Modellen ble trent med et datasett bestående av 400 videoer av vanlige tegn, merket og analysert bilde for bilde gjennom poseestimering. En responsiv nettside presenterer prosjektet og tilbyr forskningen, modellen og datasettet til gratis nedlasting. Målet er å redusere kommunikasjonsgapet.
About the A' Design Award i Jern
Ensenas Kommunikasjonsverktøy er vinner av A' Design Award i Jern, en prestisjefylt anerkjennelse som tildeles gode design som oppfyller de profesjonelle og industrielle kravene man forventer av veldesignede skaperverk. Jernvinnere viser stor dyktighet, høy spesialisering, ekspertforståelse og kreativ kapasitet hos skaperne. Ensenas Kommunikasjonsverktøy forventes å være et høyt ansett, beundret og verdsatt skaperverk som er praktisk og nyskapende. Dette designet, som har vunnet A' Design Award i Jern, integrerer bransjens beste praksis og har kompetente tekniske egenskaper knyttet til kunnskap og talent. Ensenas Kommunikasjonsverktøy respekteres for sin grundighet og er utformet for å gi forbedringer i livskvalitet som bidrar til å gjøre verden til et bedre sted.
Press Kit
- 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
