How the Brain Parses Language • Hacker News Board

Re: How the Brain Parses Language

#51

Post by tgv » Thu, Dec 11, 2025, 6:13 PM UTC

GolDDranks wrote: post #40

tgv wrote: post #8

Earlier quoted context omitted.

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.

> 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?

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.

Re: How the Brain Parses Language

#52

Post by aeve890 » Thu, Dec 11, 2025, 6:14 PM UTC

HarHarVeryFunny wrote: post #36

rdtsc wrote: post #26

> But what if our neurobiological reality includes a system that behaves something like an LLM? With every technological breakthrough we always posit that the brain has to work like the newly discovered thing. At various times brains were hydraulic, mechanical, electrical, like a computer, like a network. Now, of course, the brain has to be like an LLM.

Yes, but at least now we're comparing artificial to real neural networks, so the way it works at least has a chance of being similar. I do think that a transformer, a somewhat generic hierarchical/parallel predictive architecture, learning from prediction failure, has to be at least somewhat similar to how we learn language, as opposed to a specialized Chompyskan "language organ". The main difference is perhaps that…

>Yes, but at least now we're comparing artificial to real neural networks

Given that the only similarity between the two of is just the "network" structure I'd say that point is pretty weak. The name "artificial neural network" it's just an historical artifact and an abstraction totally disconnected from the real thing.

Re: How the Brain Parses Language

#53

Post by trebligdivad » Thu, Dec 11, 2025, 6:25 PM UTC

liampulles wrote: post #9

What I'm curious about is what the language parts of the human brain look like for babies and toddlers. Humans obviously have a bunch of languages they can speak, and toddlers pick up the language that their guardians speak around their home, so there seems to be machinery there that is for the task of "online" learning.

I'd like one stage further - what are the genetics of this area? How does a dedicated brain area like this get encoded - (Hopefully the Allen Institute might dig on this one?); but if we can find how the areas are encoded in the DNA we could presumably see how they evolved, but then perhaps also spot other areas?

Re: How the Brain Parses Language

#54

Post by retrac » Thu, Dec 11, 2025, 6:27 PM UTC

adamzwasserman wrote: post #19

There's an interesting falsifiable prediction lurking here. If the language network is essentially a parser/decoder that exploits statistical regularities in language structure, then languages with richer morphological marking (more redundant grammatical signals) should be "easier" to parse — the structure is more explicitly marked in the signal itself. French has obligatory subject-verb agreement, gender marking on…

That presumes that languages with little morphology do not have equivalent structures at work elsewhere doing the same kind of heavy lifting.

One classic finding in linguistics is that languages with lots of morphology tend to have freer word order. Latin has lots of morphology and you can move the verb or subject anywhere in the sentence and it's still grammatical. In a language like English syntax and word order and word choice take on the same role as morphology.

Inflected languages may indeed have more information encoded in each token. But the relative position of the tokens to each other also encodes information. And inflected languages appear to do this less.

Languages with richer morphology may also have smaller vocabularies. To be fair, this is a contested conjecture too. (It depends a lot on how you define a morpheme.) But the theory is that languages like Ojibwe or Sansrkit with rich derivational morphologies and grammatical inflections simply don't need a dozen words for different types of snow, or to describe thinking. A single morpheme with an almost infinite number of inflected forms can carry all the shades of meaning, where different morphemes might be used to make the same distinctions, in a less inflected language.

Re: How the Brain Parses Language

#55

Post by tgv » Thu, Dec 11, 2025, 6:48 PM UTC

adamzwasserman wrote: post #30

fellowniusmonk wrote: post #28

Earlier quoted context omitted.

Dyslexia seems to be more of an issue in English than other languages right? But also, maybe the difficulty of parsing recruits other/executive function and is beneficial in other ways? The per phoneme density/efficiency of English is supposed to be quite high as an emergent trade language. Perhapse speaking a certain language would promote slower more intentional parsing, humility through syntax uncertainty, maybe n…

The dyslexia point is interesting; yes, English orthography causes more reading disorders than languages with more regular spelling-to-sound mappings (Italian, Finnish, etc.). That's consistent with the parser having to work harder when the signal is noisier. Your intuition about "slower more intentional parsing" connects to something I'm exploring: we may parse language at two levels simultaneously; a fast, nearly a…

First: dyslexia has little to do with parsing, which is generally understood to relate to structure/relations between words.

Second: multiple levels of language processing have been identified, although it's not at all clear how well separated they are. The higher levels (semantics, pragmatics) are by necessity lagging behind the lower (phonetics, syntax). The higher levels also seem more "deliberate."

Re: How the Brain Parses Language

#56

Post by pessimizer » Thu, Dec 11, 2025, 7:06 PM UTC

retrac wrote: post #54

adamzwasserman wrote: post #19

There's an interesting falsifiable prediction lurking here. If the language network is essentially a parser/decoder that exploits statistical regularities in language structure, then languages with richer morphological marking (more redundant grammatical signals) should be "easier" to parse — the structure is more explicitly marked in the signal itself. French has obligatory subject-verb agreement, gender marking on…

That presumes that languages with little morphology do not have equivalent structures at work elsewhere doing the same kind of heavy lifting. One classic finding in linguistics is that languages with lots of morphology tend to have freer word order. Latin has lots of morphology and you can move the verb or subject anywhere in the sentence and it's still grammatical. In a language like English syntax and word order an…

You saved me from posting this. Strict word order makes a lot of things easier that have to be done through morphology in the vulgar Latins.

> Languages with richer morphology may also have smaller vocabularies. To be fair, this is a contested conjecture too.

I agree with the criticism of this to an extent. A lot of has seemed to me like it relies on thinking of English as a sort of normal, baseline language when it is actually very odd. It has so many vowels, and it also isn't open so has all of these little weird distinguishing consonant clusters at the end of syllables. And when you compare it to a language conjugated with a bunch of suffixes, those suffixes gradually both make the words very long, and add a bunch of sounds that can't be duplicated very often at the end of roots without causing confusion.

All of that together means that there's a lot more bandwidth for more words. English, even though it has a lot more words than other languages, doesn't have more precise words. Most of them are vague duplications, including duplicating most of Norman French just to have special, fancy versions of words that already existed. The strong emphasis on position in the grammar and the vast number of vowels also allows it to easily borrow words from other languages without a compelling reason.

I think all of that is enough to explain why English is such an outlier on vocabulary size, and I think you see similar in other languages that share a subset of these features.

Re: How the Brain Parses Language

#57

Post by seszett » Thu, Dec 11, 2025, 7:24 PM UTC

adamzwasserman wrote: post #43

Grosvenor wrote: post #39

Earlier quoted context omitted.

And we have those French/English text corpora in the form of Canadian law. All laws in Canada at the federal level are written in English and French. This was used to build the first modern language translation systems, testing them going from English->french->english. And in reverse. You could do similar here , understanding that your language is quite stilted legalese. Edit: there might be other countries with simi…

Incredibly, I had not thought to use that data set. Now I will. Thanks.

Belgian federal law is also written in Dutch, French and German, by the way.

But no English so you might not be interested.

Re: How the Brain Parses Language

#58

Post by [deleted] » Thu, Dec 11, 2025, 7:34 PM UTC

pessimizer wrote: post #56

retrac wrote: post #54

Earlier quoted context omitted.

That presumes that languages with little morphology do not have equivalent structures at work elsewhere doing the same kind of heavy lifting. One classic finding in linguistics is that languages with lots of morphology tend to have freer word order. Latin has lots of morphology and you can move the verb or subject anywhere in the sentence and it's still grammatical. In a language like English syntax and word order an…

You saved me from posting this. Strict word order makes a lot of things easier that have to be done through morphology in the vulgar Latins. > Languages with richer morphology may also have smaller vocabularies. To be fair, this is a contested conjecture too. I agree with the criticism of this to an extent. A lot of has seemed to me like it relies on thinking of English as a sort of normal, baseline language when it…

[deleted]

Re: How the Brain Parses Language

#59

Post by SAI_Peregrinus » Thu, Dec 11, 2025, 7:41 PM UTC

seanmcdirmid wrote: post #16

tcsenpai wrote: post #6

> But what if our neurobiological reality includes a system that behaves something like an LLM? It almost seems like we got inspiration from our brain to build neural networks!

It isn’t clear though. Neural networks were inspired by the brain, but transformers? It is totally plausible but do we really think just in words?

> It is totally plausible but do we really think just in words?

I find that proposition totally implausible. Some people certainly report only thinking in words & having a continuous inner monologue, but I'm not one of them. I think, then I describe my thoughts in words if I'm speaking or writing or thinking about speaking or writing.

Re: How the Brain Parses Language

#60

Post by Terretta » Thu, Dec 11, 2025, 7:44 PM UTC

GolDDranks wrote: post #5

dr_dshiv wrote: post #3

> It almost sounds like you’re saying there’s essentially an LLM inside everyone’s brain. Is that what you’re saying? >Pretty much. I think the language network is very similar in many ways to early LLMs, which learn the regularities of language and how words relate to each other. It’s not so hard to imagine, right? Yet, completely glosses over the role of rhythm in parsing language. LLMs aren’t rhythmic at all, are…

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 languag…

> 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.