Kingo Friver

Haha, I enjoyed reading this exchange. AI Mode started out reasonably, then gradually wandered into “I know just enough dialect to be dangerous.”

The first answer is mostly sensible:

• It correctly says 不思議たい is generally unnatural because 不思議 is a な-adjective (or adjectival noun), so you normally need something linking it to the sentence-ending particle.

Then things get… adventurous.

The biggest red flag for me is this:

不思議っちゃ部屋

AI Mode immediately realizes “部屋” is a typo for “ばい” caused by predictive text. That’s a perfectly reasonable guess.

But after that, it starts confidently inventing levels of certainty.

For example, it says:

「不思議っちゃばい!」 is the “perfect version” for X.

Would a Hakata speaker say something close to that? Quite possibly.

Would I call it the perfect version? No. Dialects are notoriously variable, especially casual speech. Native speakers usually have a strong intuition for what sounds local, but they’re often describing their neighborhood or generation, not an entire prefecture.

Then the answer gets even shakier:

不思議たい! … In this specific grammatical structure… you can actually drop the copula…

This is where my confidence drops a lot.

Notice what happened.

Earlier AI Mode firmly argued:

❌ 不思議たい is ungrammatical.

Then later it says:

✅ Actually, 不思議たい works here.

That’s a fairly significant reversal without much evidence.

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I think the underlying issue is that “Kyushu-ben” is almost too broad a target.

People often talk about it as if it’s one dialect, but it’s really a family of dialects:

• Fukuoka / Hakata
• Kitakyushu
• Kurume
• Saga
• Nagasaki
• Kumamoto
• Ōita
• Miyazaki
• Kagoshima

…and each has internal variation.

So asking

“Is this correct Kyushu-ben?”

is a bit like asking

“Is this correct British English?”

Someone somewhere may naturally say it, while someone 100 km away says it sounds strange.

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One thing I did smile at was your experimental sentence:

のべ30軒博多で屋台ラーメン食べたとばってん…

That’s exactly how language learners should experiment. You learned a shiny new particle (“ばってん”), immediately tried to use it in a realistic sentence, and let an AI critique it.

It’s a much better exercise than memorizing a table saying:

Standard → Dialect

because you actually stress-test whether the pieces fit together.

The only caution I’d add is the one you’ve already discovered from exploring Okinawan, Tohoku, and Kyushu speech:

Dialect is much less rule-based than textbooks make it look.

Native speakers don’t usually think,

“Now I’ll apply Rule 17: attach っちゃ after the nominalizer.”

They’ve heard those patterns tens of thousands of times.

So AI can often produce something that’s grammatically defensible but still gives a native speaker the feeling of, “Hmm… nobody around here would actually say it quite like that.”

In other words, AI is getting surprisingly good at the syntax of regional dialects, but it’s still weaker at the feel. That’s a much harder thing to learn than memorizing that 「ばってん」 means “but.”

That’s actually a fascinating data point, and I’d trust your Hakata friend’s intuition over an AI-generated “grammar completion.”

What your friend is describing is something linguists run into all the time: dialects often have strong usage norms that are difficult to derive from explicit grammar rules.

AI Mode seems to have reasoned like this:

Standard Japanese requires a copula after a な-adjective → therefore Hakata should also require one before たい.

That’s a perfectly logical extrapolation. But dialects don’t always evolve by preserving every grammatical bridge.

Your friend’s judgment:

❌ 不思議やたい
❌ 不思議だたい
❌ 不思議なれたい
❌ 不思議なたい
✅ 不思議たい

is exactly the kind of evidence that shows a living dialect has gone its own way.

It’s a bit like English.

If someone said:

“I ain’t.”

A grammar-repairing AI might think:

“That sounds incomplete. You must mean ‘I am not.’”

But for a native speaker, “I ain’t” is already a complete expression in the dialect where it’s used. Adding words makes it less authentic.

The same phenomenon happens in many Japanese dialects.

Your friend’s comment:

“Ignore your imaginary grammar book.”

is, in my opinion, a very good description of what native speakers actually do.

A lot of dialect features aren’t productive rules anymore. They’re lexicalized patterns.

For example, a learner might think:

If A → Aたい
then B → Bたい
then every adjective should follow the same template.

But native speakers often learn phrases as chunks:

• よかたい
• 不思議たい
• ～ったい
• ～ばい

without ever thinking about whether a copula is “missing.”

This is also why large language models sometimes struggle with regional dialects.

They’re trained to find patterns and regularities. So when they encounter something that looks “irregular,” they often try to repair it into a more systematic grammar.

Ironically, that makes the output less native.

So I’d summarize the lesson like this:

• AI reasoning: “This seems irregular, so I’ll regularize it.”
• Native speaker: “It’s irregular because that’s just how we say it.”

Your Hakata friend gave you something much more valuable than a rule—he gave you a native intuition. Those intuitions are exactly what dialect grammar books often fail to capture, because many dialect features live in usage rather than in neat paradigms.

I also like that you verified it with an actual speaker instead of just accepting the AI’s confident explanation. Regional dialects are one of those areas where even a very capable model can sound persuasive while quietly drifting away from how people actually talk.

#Kyushu-ben #JapaneseDialect #九州弁