Interactive Japanese-to-braille translation using case-based knowledge on the web

Authors:
Satoshi Ono;Yoshinobu Hamada;Yoshitsugu Takagi;Seiichi Nishihara;Kazunori Mizuno
Affiliations:
Institute of Information Sciences and Electronics, University of Tsukuba, Tsukuba, Ibaraki, Japan;Institute of Information Sciences and Electronics, University of Tsukuba, Tsukuba, Ibaraki, Japan;Institute of Information Sciences and Electronics, University of Tsukuba, Tsukuba, Ibaraki, Japan;Institute of Information Sciences and Electronics, University of Tsukuba, Tsukuba, Ibaraki, Japan;Institute of Information Sciences and Electronics, University of Tsukuba, Tennoudai, Tsukuba, Ibaraki, Japan
Venue:
PRICAI'00 Proceedings of the 6th Pacific Rim international conference on Artificial intelligence
Year:
2000

Citing 2
Cited 1

A Weighted Nearest Neighbor Algorithm for Learning with Symbolic Features

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Improving accuracy by combining rule-based and case-based reasoning

Artificial Intelligence

Rule- and case-based adaptive knowledge base and its application to Japanese-to-Braille translation

AIKED'07 Proceedings of the 6th Conference on 6th WSEAS Int. Conf. on Artificial Intelligence, Knowledge Engineering and Data Bases - Volume 6

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Abstract

We propose an interactive system for translating Japanese into BraiUe on the Web. Accurate automatic translation is difficult due to the ambiguous, complicated translation rules. Braille expressions must be made consistent throughout a text, even if a translation can be interpreted in more than one way. Braille translation productivity is slowed by the need for user intervention. Our system provides interactive Japaneseto-BraiUe translation and updates the knowledge base to keep results consistent and improve translation accuracy. Experimentals show that case acquisition reduces errors and that the user interface reduces output instability without requiring that the whole document be rechecked.