Abstract
AbstractThis paper showcases the work that aims at building a user-friendly mobile application of a reverse dictionary to translate sign languages to spoken languages. The concept behind the reverse dictionary is the ability to perform a video-based search by demonstrating a handshape in front of a mobile phone’s camera. The user would be able to use this feature in two ways. Firstly, the user would be able to search for a word by showing a handshape for the application to provide a list of signs that contain that handshape. Secondly, the user could fingerspell the word letter by letter in front of the camera for the application to return the sign that corresponds to that word. The user can then look through the suggested videos and see their written translations. To offer other functionalities, the application also has Search by Category and Search by Word options. Currently, the reverse dictionary supports translations from Russian Sign Language (RSL) to Russian language.
Publisher
Springer International Publishing
Reference21 articles.
1. Alonzo, O., Glasser, A., Huenerfauth, M.: Effect of automatic sign recognition performance on the usability of video-based search interfaces for sign language dictionaries. In: The 21st International ACM SIGACCESS Conference on Computers and Accessibility, pp. 56–67 (2019)
2. Bragg, D., et al.: Sign language recognition, generation, and translation: an interdisciplinary perspective. In The 21st International ACM SIGACCESS Conference on Computers and Accessibility, pp. 16–31 (2019)
3. Bragg, D., Rector, K., Ladner, R.E.: A user-powered American Sign Language dictionary. In: Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing, pp. 1837–1848 (2015)
4. Cooper, H., Pugeault, N., Bowden, R.: Reading the signs: a video based sign dictionary. In: 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), pp. 914–919. IEEE (2011)
5. Dong, C., Leu, M.C., Yin, Z.: American sign language alphabet recognition using Microsoft Kinect. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 44–52 (2015)
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