VISCOSE - a Kanji Dictionary Enriched with VISual, COmpositional, and SEmantic Information

AbstractIn this paper, we present a novel approach for building kanji dictionaries by enriching the lexical data of 3,500 kanji with images, structural decompositions, and semantically based cross-media mappings from the textual to the visual dimension. Our kanji dictionary is part of a Web-based contextual language learning environment based on augmented browsing technology. We display our multimodal kanji information as kanji cards in the Web browser, offering a versatile representation that can be integrated into other advanced creative language learning applications, such as memorization puzzles, creative storytelling assignments, or educational games.