UPSI Digital Repository (UDRep)
Start | FAQ | About
Menu Icon

QR Code Link :

Type :Article
Subject :T Technology (General)
ISBN :1615-5289
Main Author :Emmanuel, Dianes David
Additional Authors :
  • Alamoodi, Abdullah Hussein
  • Garfan, Salem Abdullah Salem
Title :Landscape of sign language research based on smartphone apps: Coherent literature analysis, motivations, open challenges, recommendations and future directions for app assessment
Hits :123
Place of Production :Tanjung Malim
Publisher :Fakulti Komputeran & Meta-Teknologi
Year of Publication :2024
Notes :Universal Access in the Information Society
Corporate Name :Universiti Pendidikan Sultan Idris
HTTP Link : Click to view web link
PDF Full Text :You have no permission to view this item.

Abstract : Universiti Pendidikan Sultan Idris
Numerous nations have prioritised the inclusion of citizens with disabilities, such as hearing loss, in all aspects of social life. Sign language is used by this population, yet they still have trouble communicating with others. Many sign language apps are being created to help bridge the communication gap as a result of technology advances enabled by the widespread use of smartphones. These apps are widely used because they are accessible and inexpensive. The services and capabilities they offer and the quality of their content, however, differ greatly. Evaluation of the quality of the content provided by these applications is necessary if they are to have any kind of real effect. A thorough evaluation like this will inspire developers to work hard on new apps, which will lead to improved software development and experience overall. This research used a systematic literature review (SLR) method, which is recognised in gaining a broad understanding of the study whilst offering additional information for future investigations. SLR was adopted in this research for smartphone-based sign language apps to understand the area and main discussion aspects utilised in the assessment. These studies were reviewed on the basis of related work analysis, main issues, discussions and methodological aspects. Results revealed that the evaluation of sign language mobile apps is scarce. Thus, we proposed a future direction for the quality assessment of these apps. The findings will benefit normal-hearing and hearing-impaired users and open up a new area where researchers and developers could work together on sign language mobile apps. The results will help hearing and non-hearing users and will pave the way for future collaboration between academicians and app developers in the field of sign language technology. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.

References

W. H. O. (WHO): Deafness and hearing loss.(accessed 21 April 2021).

Kaland, M., Salvatore, K. (2002): The psychology of hearing loss. ASHA Lead. 7(5), 4–15.

Young, A.M., Ackerman, J. (2001): Reflections on validity and epistemology in a study of working relations between deaf and hearing professionals. Qual. Health Res. 11(2), 179–189.

Jebali, M., Dakhli, A., Jemni, M. (2021):Vision-based continuous sign language recognition using multimodal sensor fusion. Evol. Syst. 1–14.

Alamoodi, A. et al. (2022):New extension of fuzzy-weighted zero-inconsistency and fuzzy decision by opinion score method based on cubic pythagorean fuzzy environment: a benchmarking case study of sign language recognition systems. Int. J. Fuzzy Syst. 1–18.

Al-Samarraay, M.S., et al. (2022): A new extension of FDOSM based on pythagorean fuzzy environment for evaluating and benchmarking sign language recognition systems. Neural Comput. Appl. 34(6), 4937–4955.

Abualigah, L. M. Q. (2019):Feature selection and enhanced krill herd algorithm for text document clustering. Springer.

Alrubayi, A.H., et al. (2021): A pattern recognition model for static gestures in malaysian sign language based on machine learning techniques. Comput. Electr. Eng. 95, 107383.

Leite, D., Škrjanc, I., Gomide, F. (2020):An overview on evolving systems and learning from stream data. Evol. Syst. 1–18.

Schliebs, S., Kasabov, N. (2013): Evolving spiking neural network—a survey. Evol. Syst. 4(2), 87–98.

Abualigah, L.M., Khader, A.T. (2017): Unsupervised text feature selection technique based on hybrid particle swarm optimization algorithm with genetic operators for the text clustering. J. Supercomput. 73(11), 4773–4795.

Dadiz, B. G., Abrasia, J. M. B., Jimenez, J. L. (2017): Go-Mo (Gomotion): an android mobile application detecting motion gestures for generating basic mobile phone commands utilizing KLT algorithm. In: 2017 IEEE 2nd International Conference on Signal and Image Processing (ICSIP), pp. 30–34, IEEE.

Alamoodi, A. et al. (2020) :A systematic review into the assessment of medical apps: motivations, challenges, recommendations and methodological aspect. Health Technol. 1–17.

Klímová, J.K.A.B. (2019): Use of smartphone applications in english language learning—a challenge for foreign language education. Educ. Sci. https:// doi. org/ 10. 3390/ educs ci903 0179.

Nanaware, T., Sahasrabudhe, S., Ayer, N., Christo, R. (2018):Fingerspelling-Indian Sign Language Training Tool. In: 2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT), pp. 330–334, IEEE.

Muzahidin, S., Rakun, E. (2020) :Text-driven talking head using dynamic viseme and DFFD for SIBI. In: 2020 7th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE), pp. 173–178, IEEE.

Villamarin, S. C. B., Morales, D. A. C., Reyes, C. A. Á., Sánchez, C. A. (2016):Application design sign language colombian for mobile devices VLSCApp (Voice Colombian sign language app) 1.0. In: 2016 Technologies Applied to Electronics Teaching (TAEE), pp. 1–5, IEEE.

Mahesh, M., Jayaprakash, A., Geetha, M. (2017) :Sign language translator for mobile platforms. In: 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 1176–1181, IEEE.

Perera, Y., Jayalath, N. Tissera, S., Bandara, O., Thelijjagoda, S. (2017):Intelligent mobile assistant for hearing impairers to interact with the society in Sinhala language. In: 2017 11th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), pp. 1–7, IEEE.


This material may be protected under Copyright Act which governs the making of photocopies or reproductions of copyrighted materials.
You may use the digitized material for private study, scholarship, or research.

Back to search page

Installed and configured by Bahagian Automasi, Perpustakaan Tuanku Bainun, Universiti Pendidikan Sultan Idris
If you have enquiries, kindly contact us at pustakasys@upsi.edu.my or 016-3630263. Office hours only.