Papers by Katsutoshi Ohtsuki

1 papers
Enabling Real-time Neural IME with Incremental Vocabulary Selection (N19-2)

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Challenge: Input method editor (IME) converts sequential alphabet key inputs to words in a target language.
Approach: They propose a neural-based language model that incrementally builds a subset vocabulary from the word lattice.
Outcome: The proposed approach achieves 50x speedup on Japanese IME benchmark without losing conversion accuracy.

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