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Construction of a Japanese Learner-Friendly Dictionary Interface

We propose a method which allows learners to look up words according to their expected, but not necessarily correct, reading. In preprocessing, we calculate the possible readings each kanji character can take and different types of phonological and conjugational changes that can occur, and associate a probability with each. Using these probabilities and corpus based frequencies we calculate a plausibility measure for each generated reading given a dictionary entry, based on the naive Bayes model. In response to a user-entered reading, we calculate the plausibility of each dictionary entry corresponding to the reading and display a list of candidates for the user to choose from. We have implemented our system in a webbased environment and are currently evaluating its usefulness to learners of Japanese.