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For what it's worth, there's a lot of work to do on Japanese input methods. To a human it may be obvious that hawotogu should become 刃を研ぐ (sharpen a/the blade),
by microcolonel 9y ago
For what it's worth, there's a lot of work to do on Japanese input methods. To a human it may be obvious that hawotogu should become 刃を研ぐ (sharpen a/the blade), and that one does not typically sharpen or hone a 歯 (tooth), 葉(leaf), 派(party/ingroup), or even 覇(~hegemony); but to a computer without topic-specific context, each of these is equally valid. One might be thankful that humans don't really say all that many different or interesting things, at least in this context.
- derefr 9y agoI don't know about "topic-specific context", but doesn't a word-granular Hidden Markov Model trained on huge amounts of text from the language let you figure out things like "given that the sentence includes 刃, 研 is the highest-scoring match"?
- microcolonel 9y agoIt does, but the suggestions will be nowhere to be found if somebody is making a novel use of words. That's what I was getting at.
- blipmusic 9y agoI didn't mean to imply otherwise. My curiosity was/is with the generation of the model in the link (especially compared to current models), hence the question in my original post. There's also pitch accent that helps with disambiguation of spoken Japanese (I should know, I accidentally called a friend seaweed for a long time).