A language universal would bring evidence to Chomsky's
controversial theories.
Language takes an astonishing variety of forms across
the world—to such a huge extent that a long-standing debate rages around the
question of whether all languages have even a single property in common. Well,
there’s a new candidate for the elusive title of “language universal” according
to a paper in this week’s issue of PNAS. All languages, the authors say,
self-organise in such a way that related concepts stay as close together as
possible within a sentence, making it easier to piece together the overall
meaning.
Language universals are a big deal because they shed
light on heavy questions about human cognition. The most famous proponent of
the idea of language universals is Noam Chomsky, who suggested a “universal
grammar” that underlies all languages. Finding a property that occurs in every
single language would suggest that some element of language is genetically
predetermined and perhaps that there is specific brain architecture dedicated
to language.
However, other researchers argue that there are
vanishingly few candidates for a true language universal. They say that there
is enormous diversity at every possible level of linguistic structure from the
sentence right down to the individual sounds we make with our mouths (that’s
without including sign languages).
There are widespread tendencies across languages, they
concede, but they argue that these patterns are just a signal that languages
find common solutions to common problems. Without finding a true universal,
it’s difficult to make the case that language is a specific cognitive package
rather than a more general result of the remarkable capabilities of the human
brain.
Self-organising systems
A lot has been written about a tendency in languages
to place words with a close syntactic relationship as closely together as
possible. Richard Futrell, Kyle Mahowald, and Edward Gibson at MIT were
interested in whether all languages might use this as a technique to make
sentences easier to understand.
The idea is that when sentences bundle related
concepts in proximity, it puts less of a strain on working memory. For example,
adjectives (like “old”) belong with the nouns that they modify (like “lady”),
so it’s easier to understand the whole concept of “old lady” if the words
appear close together in a sentence.
You can see this effect by deciding which of these two
sentences is easier to understand: “John threw out the old trash sitting in the
kitchen,” or “John threw the old trash sitting in the kitchen out.” To many
English speakers, the second sentence will sound strange—we’re inclined to keep
the words “threw” and “out” as close together as we can. This process of
limiting distance between related words is called dependency length
minimisation, or DLM.
Do languages develop grammars that force speakers to
neatly package concepts together, making sentences easier to follow? Or, when
we look at a variety of languages, do we find that not all of them follow the
same pattern?
The researchers
wanted to look at language as it’s actually used rather than make up sentences
themselves, so they gathered databases of language examples from 37 different
languages. Each sentence in the database was given a score based on the degree
of DLM it showed: those sentences where conceptually related words were far
apart in the sentence had high scores, and those where related words sat snugly
together had low scores.
Then, the researchers
compared these scores to a baseline. They took the words in each sentence and
scrambled them so that related words had random distances between them. If DLM
wasn’t playing a role in developing grammars, they argued, we should be seeing
random patterns like these in language: related words should be able to have
any amount of distance between them. If DLM is important, then the scores of
real sentences should be significantly lower than the random sentences.
They found what they
expected: “All languages have average dependency lengths shorter than the
random baseline,” they write. This was especially true for longer sentences,
which makes sense—there isn’t as much difference between “John threw
out the trash,” and “John threw the trash out”
as there is between the longer examples given above.
They also found that
some languages display DLM more than others. Those languages that don’t
rely just on word order to communicate the relationships between words tended
to have higher scores. Languages like German and Japanese have markings on nouns
that convey the role each noun plays within the sentence, allowing them to
have freer word order than English. The researchers suggest that the markings
in these languages contribute to memory and understanding, making DLM slightly
less important. However, even these languages had scores lower than the random
baseline.
The family
tree
This research adds an
important piece of the puzzle to the overall picture, says Jennifer Culbertson,
who researches evolutionary linguistics at the University of Edinburgh. It’s “an
important source of evidence for a long-standing hypothesis about how word
order is determined across the world’s languages,” she told Ars Technica.
Although the paper
only looked at 37 languages, it’s actually incredibly difficult to build these
databases of language in use, which makes it a reasonably impressive sample,
she said. There is a problem here, though: many of the languages studied are
related to one another, representing only a few of the huge number of language
families, so we’d expect them to behave in similar ways. More research is going
to be needed to control for language relatedness.
This paper joins a lot of previous work on the topic,
so it’s not the lone evidence of DLM—it’s corroborating, and adding to, a fair
bit of past research. It’s “a lot of good converging evidence,” she said.
“There are many proposed universal properties of
language, but basically all of them are controversial,” she explained. But it’s
plausible, she added, that DLM—or something like it—could be a promising candidate
for a universal cognitive mechanism that affects how languages are structured.
For a debate as sticky as the one about language
universals, there could be multiple ways of interpreting this evidence.
Proponents of Chomsky's school might argue that it's evidence for a dedicated
language module, but those who favour a different interpretation could suggest
that working memory affects all brain functions, not just language.
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