“Deep in the belly of a giant fiberglass triceratops, eight rare bats have made a home.”
–Today in “linguists are not kidding when they say that your command of English enables you to understand sentences that have never occurred before in the entire history of the human species.” (fromAtlas Obscura)
I turned my experiments back towards language again. Would it be possible to train a deep learning network for a dead language? I have in my previous art projects worked extensively with languages that are endangered or already extinct – so called dying languages[4]. Every ten days a language disappears, and at that rate, within a few generations, half of the approximately 6000 languages in the world today will be extinct. The concept of a dying language is a highly complex mechanism. In order for language to survive, it is of central importance that the language is in use, especially in normal households, and between generations of a family. Can a language be kept and conserved for future generations, or is a language alive only when actively used and spoken between people in a society? Can a language be detached from a people’s culture, knowledge and identity? Among the family of Sámi languages (of the indigenous groups of northern Norway, Sweden, Finland and Russia), several of the languages are already extinct or with very few and old speakers left, but efforts are being made to help revive some of them.
For sound complexity, one language stands out. !Xóõ, spoken by just a few thousand, mostly in Botswana, has a blistering array of unusual sounds. Its vowels include plain, pharyngealised, strident and breathy, and they carry four tones. It has five basic clicks and 17 accompanying ones. The leading expert on the !Xóõ, Tony Traill, developed a lump on his larynx from learning to make their sounds. Further research showed that adult !Xóõ-speakers had the same lump (children had not developed it yet).
Tuyuca, of the eastern Amazon has a sound system with simple consonants and a few nasal vowels, so is not as hard to speak as Ubykh or !Xóõ. Like Turkish, it is heavily agglutinating, so that one word, hóabãsiriga means “I do not know how to write.” Like Kwaio, it has two words for “we”, inclusive and exclusive. The noun classes (genders) in Tuyuca’s language family (including close relatives) have been estimated at between 50 and 140. Some are rare, such as “bark that does not cling closely to a tree”, which can be extended to things such as baggy trousers, or wet plywood that has begun to peel apart.
Most fascinating is a feature that would make any journalist tremble. Tuyuca requires verb-endings on statements to show how the speaker knows something. Diga ape-wi means that “the boy played soccer (I know because I saw him)”, while diga ape-hiyi means “the boy played soccer (I assume)”. English can provide such information, but for Tuyuca that is an obligatory ending on the verb. Evidential languages force speakers to think hard about how they learned what they say they know.
The film turns on the visual language of the heptapods, the name given to the aliens because of their seven tentacular feet. In Chiang’s short story, the spoken language looks pretty familiar to Dr Banks; nouns have special markers, similar to the grammatical cases of Latin or German, that signify meaning; there are words, and they seem to come in particular orders depending on what their function is in the grammar of the sentence. But it is the visual language that is at the heart of the story. This language, as presented in the film, is just beautiful; the aliens squirt some kind of squid-like ink into the air which resolves holistically into a presentation of the thought they want to express. It looks like a circular whorl drawn with complex curlicues twisting off of the main circumference. The form of the language is not linear in any sense. The whorls emerge simultaneously as wholes. The orientation, shape, modulation, and direction of the tendrils that build the whorls serve to convey the meaningful connections of the parts to the whole. Multiple sentences can all be combined into more and more complex forms that, in the film, require GPS style computer analysis. The atemporality and multidimensionality of the heptapods’ written language is a core part of the plot. So, could a human language work like this, or is that just too alien?
Pretty much every metaphor designer is inspired by Metaphors We Live By (1980), by the Berkeley linguist George Lakoff and the philosopher Mark Johnson at the University of Oregon. It’s the classic look at how metaphors structure the way we think and talk, and once you’ve read it, you can’t help but agree that, at a conceptual level, life is a journey, and arguments are wars (you take sides, there can be only one winner, evidence is a weapon). However, for the practical metaphor designer, psycholinguistic research turns out to be much more useful than philosophical commentary, because it studies how people actually encounter and process new metaphors.
For each value that a language has, we calculate the relative frequency of that value for all the other languages that are coded for it. So if we had included subject-object-verb order then English would’ve gotten a value of 0.355 (we actually normalized these values according to the overal entropy for each feature, so it wasn’t exactly 0.355, but you get the idea). The Weirdness Index is then an average across the 21 unique structural features. But because different features have different numbers of values and we want to reduce skewing, we actually take the harmonic mean (and because we want bigger numbers = more weird, we actually subtract the mean from one). In this blog post, I’ll only report languages that have a value filled in for at least two-thirds of features (239 languages).
‘Language shift’ is the process whereby members of a community in which more than one language is spoken abandon their original vernacular language in favour of another. The historical shifts to English by Celtic language speakers of Britain and Ireland are particularly well-studied examples for which good census data exist for the most recent 100–120 years in many areas where Celtic languages were once the prevailing vernaculars. We model the dynamics of language shift as a competition process in which the numbers of speakers of each language (both monolingual and bilingual) vary as a function both of internal recruitment (as the net outcome of birth, death, immigration and emigration rates of native speakers), and of gains and losses owing to language shift.
