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Connecting Silent Worlds: Requirements for Automatic Oral-Sign Language Translation

Published: 18 December 2024 Publication History

Resumo

One of the challenges deaf people face when trying to access to health services is communicating with health professionals. These communication difficulties can result in health risks, such as diagnostic and treatment errors. To overcome such difficulties, it is essential to develop automatic translation systems that facilitate interaction between deaf people and healthcare professionals. The work presented in this article is inserted in the context of the project “Captar-Libras: Video communication system for the deaf applied to pre-medical care” (In Portuguese:“Captar-Libras: Sistema de Comunicação por vídeos para surdos aplicado ao pré-atendimento médico”), which aims to generate a bidirectional Portuguese-Libras translation through the use of photorealistic avatars for healthcare. This study presents a set of requirements that aim to guide the development of these systems. These requirements consider the specific needs of both deaf people and healthcare professionals.

References

[1]
Qazi Mohammad Areeb and Mohammad Nadeem. 2021. Deep Learning Based Hand Gesture Recognition for Emergency Situation: A Study on Indian Sign Language. In 2021 International Conference on Data Analytics for Business and Industry (ICDABI). IEEE, Sakheer, Bahrain, 33–36.
[2]
Letycia Bond. 2019. Surdos enfrentam dificuldade para atendimento em saúde. Retrieved May 21, 2024 from https://agenciabrasil.ebc.com.br/direitos-humanos/noticia/2019-10/surdos-enfrentam-dificuldade-para-atendimento-em-saude
[3]
Ministério da Saúde. 2019. Pesquisa Nacional em Saúde. https://www.pns.icict.fiocruz.br/wp-content/uploads/2021/12/liv101846.pdf Acessado em 17/05/2024.
[4]
Diego RB da Silva, Tiago Maritan U de Araújo, Thaís Gaudencio do Rêgo, Manuella Aschoff Cavalcanti Brandão, and Luiz Marcos Garcia Gonçalves. 2024. A multiple stream architecture for the recognition of signs in Brazilian sign language in the context of health. Multimedia Tools and Applications 83, 7 (2024), 19767–19785.
[5]
Diego R. B. da Silva, Tiago Maritan U. Araujo, Thais Gaudencio do Rêgo, and Manuella Aschoff Cavalcanti Brandão. 2020. A Two-Stream Model Based on 3D Convolutional Neural Networks for the Recognition of Brazilian Sign Language in the Health Context. In Proceedings of the Brazilian Symposium on Multimedia and the Web (São Luís, Brazil) (WebMedia ’20). Association for Computing Machinery, New York, NY, USA, 5–12.
[6]
Haritha V Das, Kavya Mohan, Linta Paul, Sneha Kumaresan, and Chitra S Nair. 2024. Transforming consulting atmosphere with Indian sign language translation. Multimedia Tools and Applications 83, 5 (2024), 13543–13555.
[7]
Dianes David, AH Alamoodi, OS Albahri, Salem Garfan, AS Albahri, BB Zaidan, and Juliana Chen. 2024. Sign language mobile apps: a systematic review of current app evaluation progress and solution framework. Evolving Systems 15, 2 (2024), 669–686.
[8]
Jane Eire Silva Alencar de Menezes e Cléia Rocha de Sousa Feitosa. 2017. Língua Brasileira de Sinais (LIBRAS). http://educapes.capes.gov.br/handle/capes/176804. Acessado em 18/05/2024.
[9]
Maartje De Meulder. 2021. Is “good enough” good enough? Ethical and responsible development of sign language technologies. In Proceedings of the 1st International Workshop on Automatic Translation for Signed and Spoken Languages (AT4SSL), Dimitar Shterionov (Ed.). Association for Machine Translation in the Americas, Virtual, 12–22. https://aclanthology.org/2021.mtsummit-at4ssl.2
[10]
Vanessa Duarte de Souza, Amanda Geyse Hoeckele, Maria Luiza Costa Borim, Heloa Costa Borim Christinelli, and Maria Antônia Ramos Costa. 2020. Percepção de surdos sobre o atendimento nos serviços de saúde. Brazilian Journal of Development 6, 8 (2020), 55347–55356.
[11]
Mustapha Deji Dere, Roshidat Oluwabukola Dere, Adewale Adesina, and Aliyu Rufai Yauri. 2022. SmartCall: A Real-time, Sign Language Medical Emergency Communicator. In 2022 5th Information Technology for Education and Development (ITED). IEEE, Abuja, Nigeria, 1–6.
[12]
Uzma Farooq, Mohd Shafry Mohd Rahim, Nabeel Sabir, Amir Hussain, and Adnan Abid. 2021. Advances in machine translation for sign language: approaches, limitations, and challenges. Neural Computing and Applications 33, 21 (2021), 14357–14399.
[13]
Yunqi Guo, Jinghao Zhao, Boyan Ding, Congkai Tan, Weichong Ling, Zhaowei Tan, Jennifer Miyaki, Hongzhe Du, and Songwu Lu. 2023. Sign-to-911: Emergency Call Service for Sign Language Users with Assistive AR Glasses. In Proceedings of the 29th Annual International Conference on Mobile Computing and Networking. Association for Computing Machinery, New York, NY, USA, 1–15.
[14]
Basma Hisham and Alaa Hamouda. 2019. Supervised learning classifiers for Arabic gestures recognition using Kinect V2. SN Applied Sciences 1, 7 (2019), 768.
[15]
Luis Naranjo-Zeledón, Jesús Peral, Antonio Ferrández, and Mario Chacón-Rivas. 2019. A systematic mapping of translation-enabling technologies for sign languages. Electronics 8, 9 (2019), 1047.
[16]
Jakob Nielsen. 1994. Heuristic evaluation. In Usability Inspection Methods, Jakob Nielsen and Robert L. Mack (Eds.). John Wiley & Sons, Inc., New York, NY, USA, 25–62.
[17]
World Health Organization. 2021. World report on hearing. Technical Report. Geneva: World Health Organization. Licence: CC BY-NC-SA 3.0 IGO. Acessado em 17/05/2024.
[18]
Regiane Ferreira Rezende, Leonor Bezerra Guerra, and Sirley Alves da Silva Carvalho. 2021. The perspective of deaf patients on health care. Revista CEFAC 23 (2021), e0620.
[19]
Jampierre Rocha, Jeniffer Lensk, Taís Ferreira, and Marcelo Ferreira. 2020. Towards a Tool to Translate Brazilian Sign Language (Libras) to Brazilian Portuguese and Improve Communication with Deaf. In 2020 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). 1–4.
[20]
Julia Manuela G. Soares, Isabel F. de Carvalho, Elidéa L. A. Bernardino, Milena Soriano Marcolino, and Raquel Oliveira Prates. 2024. An Evaluation of Portuguese to Libras Translator Apps Applied to the Medical Context. In Universal Access in Human-Computer Interaction, Margherita Antona and Constantine Stephanidis (Eds.). Springer Nature Switzerland, Cham, 290–304.
[21]
Candy Obdulia Sosa-Jiménez, Homero Vladimir Ríos-Figueroa, and Ana Luisa Solís-González-Cosío. 2022. A prototype for Mexican sign language recognition and synthesis in support of a primary care physician. IEEE Access 10 (2022), 127620–127635.
[22]
Annie G Steinberg, Steven Barnett, Helen E Meador, Erin A Wiggins, and Philip Zazove. 2006. Health care system accessibility: experiences and perceptions of deaf people. Journal of general internal medicine 21 (2006), 260–266.
[23]
J. Alfredo Sánchez, Soraia Prietch, and Josué I. Cruz-Cortez. 2022. Natural Sign Language Interfaces for Deaf Users: Rationale and Design Guidelines. In 2022 IEEE Mexican International Conference on Computer Science (ENC). 1–7.
[24]
Nina Tran, Richard E. Ladner, and Danielle Bragg. 2023. U.S. Deaf Community Perspectives on Automatic Sign Language Translation. In Proceedings of the 25th International ACM SIGACCESS Conference on Computers and Accessibility (, New York, <state>NY</state>, USA,) (ASSETS ’23). Association for Computing Machinery, New York, NY, USA, Article 76, 7 pages.
[25]
Kun Xia, Weiwei Lu, Hongliang Fan, and Qiang Zhao. 2022. A sign language recognition system applied to deaf-mute medical consultation. Sensors 22, 23 (2022), 9107.

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  1. Connecting Silent Worlds: Requirements for Automatic Oral-Sign Language Translation

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        IHC '24: Proceedings of the XXIII Brazilian Symposium on Human Factors in Computing Systems
        October 2024
        1070 pages
        ISBN:9798400712241
        DOI:10.1145/3702038
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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        Published: 18 December 2024

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        Author Tags

        1. Automatic translation
        2. Brazilian sign language
        3. Libras
        4. Portuguese
        5. deaf user
        6. accessibility
        7. healthcare

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