Ensenas رابطے کا آلہ by Saeli Seira Saenz and Alana Betanzo Carriles

Ensenas رابطے کا آلہ by Saeli Seira Saenz and Alana Betanzo Carriles is a highly esteemed winner of the very prestigious 2023 A' Design Award آہنی انعام in سماجی ڈیزائن Competition Category.

لوہاسماجی· 2023

Ensenas رابطے کا آلہ

by Saeli Seira Saenz and Alana Betanzo Carriles

Client: Universidad de Monterrey

A' Design Award آہنی انعام Winner in سماجی Category

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Colors

The Design

About Ensenas رابطے کا آلہ

اینسیناس ایک ڈیجیٹل آلہ ہے جو میکسیکو میں سماعت سے محروم افراد اور سننے والے افراد کے درمیان رابطے کو بہتر بنانے کے لیے تیار کیا گیا ہے۔ اینسیناس ایک مشین لرننگ ماڈل استعمال کرتا ہے جو میکسیکن سائن لینگویج (اشاراتی زبان) کو حقیقی وقت میں پڑھتا ہے اور الفاظ کو تحریری ہسپانوی زبان میں ترجمہ کرتا ہے۔ اس ماڈل کی تربیت عام اشارات کی 400 ویڈیوز کے ڈیٹا سیٹ سے کی گئی، جنہیں پوز ایسٹیمیشن کے ذریعے فریم بہ فریم لیبل اور تجزیہ کیا گیا۔ ایک ریسپانسو ویب سائٹ اس منصوبے کو پیش کرتی ہے اور تحقیق، ماڈل اور ڈیٹا سیٹ مفت ڈاؤن لوڈ کے لیے فراہم کرتی ہے۔ مقصد رابطے کے خلا کو کم کرنا ہے۔

The Recognition

About the A' Design Award آہنی انعام

Ensenas رابطے کا آلہ A' Design Award آہنی انعام کا فاتح ہے، جو ان اچھے ڈیزائنز کو دیا جانے والا باوقار اعتراف ہے جو اچھی طرح ڈیزائن کی گئی تخلیقات سے متوقع پیشہ ورانہ اور صنعتی تقاضوں کو پورا کرتے ہیں۔ آہنی انعام کے فاتحین اپنے تخلیق کاروں کی عظیم مہارت، اعلیٰ تخصص، ماہرانہ فہم اور تخلیقی صلاحیت کو ظاہر کرتے ہیں۔ Ensenas رابطے کا آلہ سے توقع کی جاتی ہے کہ وہ ایک نہایت قدر کی جانے والی، سراہی جانے والی اور عزیز تخلیق ہوگا جو عملی اور جدید ہے۔ A' Design Award آہنی انعام جیتنے والا یہ ڈیزائن صنعت کے بہترین طریقوں کو یکجا کرتا ہے اور مہارت اور ہنر سے جڑی ہوئی قابل تکنیکی خصوصیات رکھتا ہے۔ Ensenas رابطے کا آلہ اپنی باریک بینی کی وجہ سے قابل احترام ہے اور معیار زندگی کی ایسی بہتری فراہم کرنے کے لیے ڈیزائن کیا گیا ہے جو دنیا کو ایک بہتر جگہ بنانے میں مدد دیتی ہے۔

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