Show HN: Context-aware Japanese furigana using Sudachi and ModernBERT
epitrochoid413
32 points
17 comments
May 29, 2026
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Discussion Highlights (6 comments)
epitrochoid413
I built a context-aware furigana converter for Japanese text, files, and web pages. The main problem I wanted to solve was that simple dictionary-based furigana works well for common cases, but breaks on words where the reading depends on context: * 市場: いちば or しじょう * 大分: おおいた or だいぶ * 人気: にんき or ひとけ * 最中: さいちゅう or さなか or もなか * 方: かた or ほう The engine is a hybrid system: * Sudachi for tokenization, base forms, POS, and candidate readings * Expanded dictionary coverage for compounds and fixed expressions * Custom rules for counters, suffixes, rendaku patterns, and phrase overrides * ModernBERT fallback for 144 especially context-dependent target words I have been testing it against an LLM-assisted benchmark of 7,500 Japanese lines. On the current benchmark, it gets about 12 wrong readings per 1,000 tokens. I treat that as a practical regression benchmark rather than a formal academic evaluation, but it has been useful for comparing versions and catching regressions. The hardest remaining cases are personal names, place names, rendaku, rare vocabulary, and domain-specific terms. I would especially appreciate examples where it gets the reading wrong, since those are the most useful for improving the system.
altilunium
It really works. Very cool. I’ve been looking for this kind of service for a long time since I started learning Japanese, and I’ve rarely been satisfied with the available services.
bluechair
Fantastic tool and love the delivery; no sign up required. Interested to hear how you pulled that off. Also interested to hear if you plan to eventually support an option to add pitch accent; I've never seen what training material exists for that or how that is supported in unicode.
k-taro56
I’m Japanese. I was surprised that it was able to answer correctly even when I entered commonly seen difficult-to-read place names. However, there seem to be cases where it may incorrectly read “今日” when it should be read as “こんにち.” Example: 今日の日本社会では、少子高齢化が大きな課題となっている。 Also, it’s disappointing that Japanese does not appear even when I select it. Please let me know if there’s anything I can do to help.
sollniss
Uh, in 田中さんは今何をしている, 今何 comes out as こんなに.
uasi
Got an incorrect result on my first try. Input was 振り仮名変換器の性能が如何程か試してみよう. It returned 如何(どう)程(ほど) instead of 如何(いか)程(ほど). Regardless, I'm impressed with the tool!