[GolDDranks]

I think it's obvious that she means that it's something _like_ LLMs in some aspects. You are correct in that rhythm and intonation are very important in parsing language. (And also an important cue when learning how to parse language!) It's clear that the human language network is not like LLM in that sense. However, it _is_ a bit like an _early_ LLM (remember GPT2?) in the sense that it can produce and parse language, not that it makes much deeper sense in it.

[tgv]

However ... language production and perception are quite separated in our heads. There's basically no parallel to LLMs. Note that the article doesn't give any, and is extremely vague about the biological underpinnings of language.

[GolDDranks]

> language production and perception are quite separated in our heads

Do you have any evidence for this?

I am a former linguistics student (got my masters), and, after years of absenteeism in academia, interested in the current state of the affairs. So: "quite separated in our heads" Evidence for? against?

[tgv]

Afasia, and general measures of "normal" performance.

There are various kinds of afasia, often linked to specific brain areas (Wernicke's and Broca's are well-known). And M/EEG and fMRI research suggests similar distinctions. It is difficult to reconcile with the idea that there is only one language system.

And you will also have noticed that your skills in perception and production differ. You can read/listen better than write/speak. Timing, ambiguity and errors in perception and production differ.

And more logically: the tasks are very different. In perception, you have to perceive the structure and meaning from a highly ambiguous, but ordered input of sound triggering auditory nerves, while during production, meaning is given (in non-linear order), and you have to find a way to fit it in a linear, grammatical order with matching words, which then have to be translated to muscle movements.

[GolDDranks]

Ah, totally agreed. At least there is a clear auditory / motor part in the tasks that seems quite separate.

However, I find it also unlikely that the networks are totally separate, and I wonder if there are any evidence of areas that encode the "core/abstract" linguistic de/serialization (multidimensional and messy internal semantic information ←→ linear morphophonological information) both ways, or at least mechanism that manages to use gained input network competence to "train" or "manage" output network competence.

Why? Because even though, as you say, there is a differing performance in perception and production, there is also plenty of evidence of gaining linguistic competence from input, and then managing to convert that to performance in output.

[Terretta]

> It's clear that the human language network is not like LLM in that sense.

Is it though? If rhythm or tone changes meaning, then just add symbols for rhythm and tone to LLM input and train it. You'll get not just words out that differ based on those additional symbols wrapping words, but you'll also get the rhythm and tone symbols in the output.