So Thai is the current meta
Syllables can vary in length. Japanese has very short syllables while English has rather long ones. Counting phonemes would make more sense
Wonder how Thai is the zipfile of languages.
It is multiplexed with five tones and a variety of different registers to signify relationship, status, and variable interplay between the two based on situation.
- University Thai language learner, linguist, and professional Thai reading, writing, speaking in Thailand for several years
My very casual understanding is that grammatical structure or gender isn’t really a thing, or articles for that matter, making it very contextual and tonal language so a zipfile isn’t even a bad metaphor.
However, in this case it seems like the human brain is the default Windows zip program.
I am curious about Arabic. I feel like it should be having the highest information rate.
What makes you think that? I’m curious. I would’ve assumed something like Inuktitut (1 word conveys subject verb object tense …) or something like toki pona (removes unused information) or maybe a highly analytical language like one of the Chinese languages.
I was comparing Arabic to other languages with the most speakers in the world. I have no idea what those languages you mentioned sound like. And I bet conlangs could be designed to fulfill such requirements as well.
Cowards left out Navajo.
It’s long been suspected that Koreans are really fast with rhythm games and have high APM because of their language getting to the point faster.
As someone who speaks both French and English, I’m surprised to see French as leading “information density” language. Most French terms have been incorporated into English. Language tends to be behind on technology terms. Language doesn’t have any noticeable difference in short syllable common words to English. It also seems to me that French speakers have an easier time in being vague. I have the impression that English is more precise.
Both were massive empires. Makes sense that imperialism would put selective pressure on language. Historically you’re either limited in words by space on a paper or what can be easily repeated by messengers.
I feel like the multitude of tenses in French help with being more precise.
The tenses don’t add precision, IMO. There is a plural them instead of him/her but it sounds the same as the singular him/her. There is a plural you that sounds different, but there is also a polite singular you that is the plural you.
I had the same feeling. I honestly just feel like English is a junk drawer of depth borrowing various languages, but maybe average speakers don’t try to dig deep into it?
In most cases, being vague requires more informational transfer. To be vague but still connected to whatever is the signified, you need to give more information around the idea rather than simply stating the idea. Think about being vague about how you feel versus being blunt about it.
Looking at the two curves, it looks like they are pretty close but French edges out English because of the speed it’s spoken at.
Even when it was fresh in my mind, I was never able to follow French tv because they just go so fast.
Yeah like “qu’est-ce que c’est ?” Which is just “what’s that?” (I speak both too) would never have guessed French had more information encoded, french translations are always longer too (but you don’t always pronounce all ofc).
I think this moreso demonstrates how tedious written french is. “Qu’est-ce que c’est?” is significantly faster to say than “what’s that?”
I’d wager if the chart was on information density per written letter or word french would be way further behind
Right, the spoken french could be written more or less as Kès-ke-cè.
I always thought that English was an efficient language.
Switch to Rust. I speak Rust btw.
On arch
Nah NixOS
I am pretty skeptical about these results in general. I would like to see the original research paper, but they usually
- write the text to be read in English, then translate them into the target languages.
- recurit test participants from US university campuses.
And then there’s the question of how do you measure the amount of information conveyed in natural languages using bits…
Yeah, the results are mostly likely very skewed.
This conjecture explains the results surprisingly well. If the original was written in French, which then got translated to English, which was then used as the basis of translation for the other languages that would explain the results entirely.
There’s always Google Scholar.
So I did a quick pass through the paper, and I think it’s more or less bullshit. To clarify, I think the general conclusion (different languages have similar information densities) is probably fine. But the specific bits/s numbers for each language are pretty much garbage/meaningless.
First of all, speech rates is measured in number of canonical syllables, which is a) unfair to non-syllabic languages (e.g. (arguably) Japanese), b) favours (in terms of speech rate) languages that omit syllables a lot. (like you won’t say “probably” in full, you would just say something like “prolly”, which still counts as 3 syllables according to this paper).
And the way they calculate bits of information is by counting syllable bigrams, which is just… dumb and ridiculous.
Alright, but dismissing the study as “pretty much bullshit" based on a quick read-through seems like a huge oversimplification. Using canonical syllables as a measure is actually a widely accepted linguistic standard, designed precisely to make fair comparisons across languages with different structures, including languages like Japanese. It’s not about unfairly favoring any language but creating a consistent baseline, especially when looking at large, cross-linguistic patterns.
And on the syllable omission point, like “probably” vs. “prolly," I mean, sure, informal speech varies, but the study is looking at overall trends in speech rate and information density, not individual shortcuts in casual conversation. Those small variations certainly don’t turn the broader findings into bullshit.
As for the bigram approach, it’s a reasonable proxy to capture information density. They’re not trying to recreate every phonological or grammatical nuance; that would be way beyond the scope and would lose sight of the larger picture. Bigrams offer a practical, statistically valid method for comparing across languages without having to delve into the specifics of every syllable sequence in each language.
This isn’t about counting every syllable perfectly but showing that despite vast linguistic diversity, there’s an overarching efficiency in how languages encode information. The study reflects that and uses perfectly acceptable methods to do so.
Well I did clarify I agree that the overarching point of this paper is probably fine…
widely accepted linguistic standard
I am not a linguist so apologise for my ignorance about how things are usually done. (Also, thanks for educating me.) But on the other hand just because it is the accepted way doesn’t mean it is right in this case. Especially when you consider the information rate is also calculated from syllables.
syllable bigrams
Ultimately this just measures how quickly the speaker can produce different combinations of sounds, which is definitely not what most people would envision when they hear “information in language”. For linguists who are familiar with the methodology, this might be useful data. But the general public will just get the wrong idea and make baseless generalisations - as evidenced by comments under this post. All in all, this is bad science communication.
But the general public will just get the wrong idea and make baseless generalisations - as evidenced by comments under this post. All in all, this is bad science communication.
Perhaps, but to be clear, that’s on The Economist, not the researchers or scholarship. Your criticisms are valid to point out, but they aren’t likely to be significant enough to change anything meaningful in the final analysis. As far as the broad conclusions of the paper, I think the visualization works fine.
What you’re asking for in terms of methods that will capture some of the granularity you reference would need to be a separate study. And that study would probably not be a corrective to this paper. Rather, it would serve to “color between the lines” that this study establishes.
I take your point without complaint, but I still think you’re an alien for saying “prolly”
I mean, probs. It’s right there. Use that if you have to
it’s pro^b - ly
The graph is missing languages such as Portuguese and Arabic.
That was the issue I had with my elementary school spanish teacher. He spoke so fast that you just couldn’t latch onto anything. It just sounded like DDDDDDDDDDDDDDDDS aqui. DDDDDDDDDDDDDDDDRS agostos.
So if I’m reading this right, French (closely followed by English) tends to convey the most info per unit time?
I think i read a study long ago, about the speed of transmiting information being faster in languagues of great empires. Sounds logical to me and matches English, French, Chinese.
As a french, I’m very surprised by this, as when I see a text in French side-by-side with its English translation, the English version is usually shorter. It may be a difference between speech and text, but it’s still surprising.
I really thought the information density of French was pretty low, compared to English or Breton, for example.
spoiler
as a fr*nch 🤢
Spoiler didnt work ;)
Spoiler worked perfectly 🤮
Written French is slow (needs more words )
Spoken French IS faster
Yes but they also utilize smell.
I’d like a visual of how much unnecessary elaboration different languages commonly use to make a point.
Though you can elaborate excessively for fun but how much is common?
And on the other end of the scale text speak is often extremely concise (not me tho ha). Would be cool to see and compare the limits.Yeah but 30% of the information in French are the “uhhh’s” lmao
They solved that by not pronouncing half the language.
English is pictured as such a smooth, almost perfectly normalized bell curve. On one hand it’s such a versatile language that (largely due to colonialism) has undergone so much evolution and mixing with other languages that I can believe that. On the other hand it looks almost too normal. Odd.
On the other hand it looks almost too normal. Odd.
It could indicate bias on the part of the researchers. I haven’t read their methodology, but in my amateur study of languages, some languages have some interesting tricks for communication that don’t translate to English well or efficiently. If English was used as the baseline, then the study ma not incorporate some of the neat things other languages can do as points to measure.
Mandarin has a word particle to communicate “completed action”. This is used instead of conjugating verbs for tenses. Example: in English you might say:
“I went to the shop” 5 syllables
In Mandarin the literal translation back to English would be:
“I go to the shop [completed action]” 5 syllables
For the two measures listed of essentially Information Density and Speech Velocity, this benefit wouldn’t show up, but if you’re measure for something like Encoding and Decoding Burden (I’m making up these terms), then Mandarin could rank higher.
Looking up the article the baseline is French and English I’d say. So it might be biased, but I didn’t read the article and even if I did, I’m a chemical engineer so what do I know of this field.
Could be bias. But, I wonder if it could be because English has borrowed so much from other languages.
It’s also interesting that English and French look so similar in the graphs. Both, have been the de facto international language for a long time.
