In this study, we introduce e-learning system called CASLL and demonstrate the small interface in order to implement it into the mobile video reproducers. As one of our series of previous studies for developing human interface by using Japanese Sign Language (JSL) contents [2, 3, 4], we proposed a new learning program and compare it with the existing learning program implemented in the Computer Assisted Sign Language Learning (CASLL) system [1]. In the existing learning program, users learn sign words and then try to select the appropriate Japanese translations in a natural conversation expressed by two native signers. In the proposed program, users try to segment each word from a stream of signing by manipulating a control knob on the bottom of a movie screen, and then do the same tasks in the existing learning model. The end of the segmentation task is to know how continuous signs are articulated in the natural discourse. Ten Japanese learners participated in the experiments. Five subjects learned the existing word learning program and the other five subjects learned the proposed segmentation learning program. The mean accuracy rate of the proposed program was higher than that of the existing program. The result has indicated that focusing on transitional movements has an effect for learning JSL as a second-language. Although the segmentation learning method has been shown as more effective learning method compared to the word learning program by which learners need to just memorize the meaning of words, there were some technical problems. Some learners answered that they could not see each JSL movies at once by using their own laptops to conduct the learning programs. Therefore, we needed to improve how to show JSL movies by using different sizes of screen. We define the size of movie screen as small as possible, and develop use-friendly interface with which learners can recognize whole serious of JSL movies by switching each movie side by side. We will demonstrate the interface development and see if the interface is applicable to the other sign languages. References [1] Saori Tanaka, Yosuke Matsusaka, Kuniaki Uehara: “Segmentation Learning Method as a Proposal for Sign Language e-learning”, Human Interface, 2006 (in Japanese) [2] Saori Tanaka, Kaoru Nakazono, Masafumi Nishida, Yasuo Horiuchi, Akira Ichikawa: Analysis of Interpreter's Skill to Recognize Prosody in Japanese Sign Language, Journal of Japanese Society for Artificial Intelligence (in press). [3] Kaoru Nakazono, Saori Tanaka: Study of Spatial Configurations of Equipment for Online Sign Interpretation Service, IEICE Transaction on Information and System (in press) [4] Saori Tanaka: A Study of Non-linguistic Information in Japanese Sign Language and its Application for Assisting Learners and Interpreters, Ph.D thesis, Chiba University, 2008
@inproceedings{tanaka:08016:sign-lang:lrec,
author = {Tanaka, Saori and Matsusaka, Yosuke and Nakazono, Kaoru},
title = {Interface Development for Computer Assisted Sign Language Learning: Compact Version of {CASLL}},
pages = {178--184},
editor = {Crasborn, Onno and Efthimiou, Eleni and Hanke, Thomas and Thoutenhoofd, Ernst D. and Zwitserlood, Inge},
booktitle = {Proceedings of the {LREC2008} 3rd Workshop on the Representation and Processing of Sign Languages: Construction and Exploitation of Sign Language Corpora},
maintitle = {6th International Conference on Language Resources and Evaluation ({LREC} 2008)},
publisher = {{European Language Resources Association (ELRA)}},
address = {Marrakech, Morocco},
day = {1},
month = jun,
year = {2008},
language = {english},
url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/08016.pdf}
}