Ensenas Kayan Aikin Sadarwa daga Saeli Seira Saenz and Alana Betanzo Carriles

Zane Ensenas Kayan Aikin Sadarwa daga Saeli Seira Saenz and Alana Betanzo Carriles mai nasara ne mai daraja sosai na 2023 Kyautar A' Design Award ta Baƙin Ƙarfe a Rukunin Gasar Zamantakewa.

Baƙin ƘarfeZamantakewa· 2023

Ensenas Kayan Aikin Sadarwa

daga Saeli Seira Saenz and Alana Betanzo Carriles

Abokin Ciniki: Universidad de Monterrey

Mai Nasarar Kyautar A' Design Award ta Baƙin Ƙarfe a Rukunin Zamantakewa

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Mai Nasara da Aka Tabbatar

Tabbatar da Matsayin Kyauta na #149366

Ziyarci Shafin Duba a A' Design Award Sanarwar Manema Labarai Alamar Kyauta

Launuka

Ƙirar

Game da Ensenas Kayan Aikin Sadarwa

Ensenas kayan aiki ne na dijital da aka kirkira domin inganta sadarwa tsakanin mutane masu naƙasar ji da masu jin magana a Mexico. Ensenas na amfani da tsarin koyon inji (machine learning) wanda ke karanta Harshen Kurame na Mexico (Mexican Sign Language) a lokaci na ainihi, sannan ya fassara kalmomi zuwa rubutaccen Sifaniyanci. An horar da wannan tsarin ta amfani da bayanan bidiyo 400 na alamomin da aka fi amfani da su, waɗanda aka yiwa alama kuma aka bincika firam-bi-firam ta hanyar kimanta yanayin jiki (pose estimation). Akwai gidan yanar sadarwa mai saurin daidaitawa (responsive website) wanda ke gabatar da aikin, tare da bayar da damar sauke bincike, tsarin, da bayanan da aka tara kyauta. Manufar aikin ita ce a rage gibin sadarwa.

Amincewa

Game da Kyautar A' Design Award ta Baƙin Ƙarfe

Zanen Ensenas Kayan Aikin Sadarwa ya lashe Kyautar A' Design Award ta Baƙin Ƙarfe, wata karramawa mai daraja da ake bai wa kyawawan zane-zane waɗanda ke cika buƙatun ƙwararru da masana'antu da ake tsammani daga ƙirƙire-ƙirƙire da aka tsara da kyau. Waɗanda suka lashe kyautar Baƙin Ƙarfe suna nuna babban ƙwarewa, ƙwarewa ta musamman, fahimtar ƙwararru da ikon ƙirƙira na masu ƙirƙirar su. Ana sa ran zanen Ensenas Kayan Aikin Sadarwa ya zama ƙirƙira da ake girmamawa sosai, ake sha'awa da ƙauna wacce ke da amfani kuma mai sababbin abubuwa. Wannan zane da ya lashe Kyautar A' Design Award ta Baƙin Ƙarfe yana haɗa mafi kyawun ayyukan fannin kuma yana da halayen fasaha masu cancanta da ke da alaƙa da sanin yadda da baiwa. Ana girmama zanen Ensenas Kayan Aikin Sadarwa saboda cikakkiyar kulawarsa kuma an tsara shi don ba da ingantuwar rayuwa da ke taimakawa wajen mai da duniya wuri mafi kyau.

Bayan Ƙirar

Kayan Manema Labarai

Bayanin ƙungiyar, membobinta da cikakkun bayanai na fasaha da mai ƙirar ya bayar.

Siffofi Na Musamman: 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.
Girma da Fakitin: This is a model in a website, whit a responsive design.
Kalmomin Alama: IA, Machine Learning, LSM, Data base, Service Design, education and tools, Sign Language,
Fasahar Samarwa: 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.
Ƙalubalen Zane: 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.
Bincike: 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.
Wahayi: 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.
Tsawon Lokacin Aikin: 6 months on Universidad de Montery and Monterrey City in México
Mambobin Ƙungiya: Saeli Seira Sáenz
Alana Betanzo Carriles