Ensenas Sesebediswa sa Puisano ka Saeli Seira Saenz and Alana Betanzo Carriles

Moralo oa Ensenas Sesebediswa sa Puisano ka Saeli Seira Saenz and Alana Betanzo Carriles ke mohlodi oa khau e hlomphehang haholo ya 2023 Moputso oa Tšepe oa A' Design Award Mokhahleong oa Tlhodisano oa Moralo wa Setjhaba.

TšepeSetjhaba· 2023

Ensenas Sesebediswa sa Puisano

ka Saeli Seira Saenz and Alana Betanzo Carriles

Moreki: Universidad de Monterrey

Mohlodi oa Moputso oa Tšepe oa A' Design Award Mokhahleong oa Setjhaba

35,348

Mohlodi oa Khau ea Netefaditsweng

Netefatsa Boemo ba Khau bakeng sa #149366

Etela Sebaka Sheba ho A' Design Award Tokollo ya Boraditaba Baeche ya Moputso

Mebala

Moralo

Mabapi le Ensenas Sesebediswa sa Puisano

Ensenas ke sesebediswa sa dijithale se entsweng ho ntlafatsa puisano pakeng tsa batho ba nang le bokoaladitsebe le batho ba utlwang naheng ya Mexico. Ensenas e sebedisa mmotlolo wa boithuto ba metjhini o balang Puo ya Matsoho ya Mexico (Mexican Sign Language) ka nako ya nnete mme o fetolela mantswe ho Sepanishe se ngotsweng. Mmotlolo ona o kokobelitswe ka sete ya data ya divideo tse 400 tsa matshwao a tlwaelehileng, tse ngotsweng dileibole le ho hlahlojwa lera ka lera ka mokgwa wa pose estimation. Websaete e ikamahanyang le didivaese e hlahisa morero ona mme e fana ka patlisiso, mmotlolo le sete ya data hore di jarollwe mahala. Sepheo ke ho fokotsa lekgalo la puisano.

Kamohelo

Mabapi le Moputso oa Tšepe oa A' Design Award

Ensenas Sesebediswa sa Puisano ke mohapi oa Moputso oa Tšepe oa A' Design Award, kananelo e hlomphehang e fuoang meralo e metle e finyellang litlhoko tsa porofeshenale le tsa indasteri tse lebelletsoeng ho lintho tse hlahisitsoeng tse entsoeng hantle. Bahapi ba Tšepe ba bontša bokhoni bo boholo, bokhethehi bo phahameng, kutloisiso ea litsebi le bokhoni ba boqapi ba baqapi ba bona. Ensenas Sesebediswa sa Puisano e lebelletsoe ho ba ntho e hlahisitsoeng e hlomphuoang haholo, e ratoang le e ratehang, e sebetsang le e nang le mehopolo e mecha. Moralo ona o hapileng Moputso oa Tšepe oa A' Design Award o kenyelletsa mekhoa e metle ka ho fetesisa ea indasteri mme o na le litšobotsi tsa theknoloji tse nang le bokhoni tse amanang le tsebo le talenta. Ka lebaka la botlalo ba eona, Ensenas Sesebediswa sa Puisano e tšoanelehela tlhompho mme e entsoe ho fana ka ntlafatso ea bophelo e thusang ho etsa hore lefatše le be sebaka se molemo.

Ka Mora Moralo

Sete ya Boraditaba

Litlhaku, ditho tsa sehlopha le lintlha tsa botekgeniki tse fanoeng ke moetsi wa moralo.

Boleng bo Ikhethang: 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.
Boholo le Phuthelo: This is a model in a website, whit a responsive design.
Lithegi: IA, Machine Learning, LSM, Data base, Service Design, education and tools, Sign Language,
Theknoloji ya Tlhahiso: 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.
Phephetso ya Moralo: 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.
Dipatlisiso: 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.
Kgothaletso: 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.
Nako ya Projeke: 6 months on Universidad de Montery and Monterrey City in México
Litho tsa Sehlopha: Saeli Seira Sáenz
Alana Betanzo Carriles