Everything so far is bilingual JA–EN. Real multilingual workplaces in Japan routinely involve a third language, and the script-accuracy framing generalises naturally — it is defined per-language, not per-pair.
Why it is interesting
- Script accuracy scales to N languages without redefinition: the metric asks whether each language's words land in that language's script. A trilingual extension is a real test of whether the metric is principled or was tuned to a two-language case.
- Script-distinct triples are the strongest test: JA–EN–KO (kanji/kana, Latin, Hangul) or JA–EN–ZH (the hard case — kanji and hanzi share glyphs, so script alone cannot disambiguate).
- CS-FLEURS covers 113 code-switched pairs across 52 languages, so evaluation data for several triples partly exists.
Open questions worth a paper
- Does encoder LoRA still carry the gains at three languages, or does capacity become the binding constraint?
- Does adding a third language degrade the first two, and does the balanced-mix trick that fixed Japanese forgetting still work?
- Does JA–ZH break script accuracy, given shared characters? If so, what replaces it?
Suggested scope
Start with JA–EN–KO: three visually distinct scripts, good FLEURS coverage, and a clean test of whether the method generalises before tackling the JA–ZH ambiguity.
Everything so far is bilingual JA–EN. Real multilingual workplaces in Japan routinely involve a third language, and the script-accuracy framing generalises naturally — it is defined per-language, not per-pair.
Why it is interesting
Open questions worth a paper
Suggested scope
Start with JA–EN–KO: three visually distinct scripts, good FLEURS coverage, and a clean test of whether the method generalises before tackling the JA–ZH ambiguity.