Tag Archives: linguistics

Ancient world dictionary finished after 90 years – an amazing project

Ancient world dictionary finished _ after 90 years

Ancient world dictionary finished _ after 90 years

(AP)  CHICAGO (AP) β€” It was a monumental project with modest beginnings: a small group of scholars and some index cards. The plan was to explore a long-dead language that would reveal an ancient world of chariots and concubines, royal decrees and diaries β€” and omens that came from the heavens and sheep livers.

The year: 1921. The place: The University of Chicago. The project: Assembling an Assyrian dictionary based on words recorded on clay or stone tablets unearthed from ruins in Iraq, Iran, Syria and Turkey, written in a language that hadn’t been uttered for more than 2,000 years. The scholars knew the project would take a long time. No one quite expected how very long.

Decades passed. The team grew. Scholars arrived from Vienna, Paris, Copenhagen, Jerusalem, Berlin, Helsinki, Baghdad and London, joining others from the U.S. and Canada. One generation gave way to the next, one century faded into the next. Some signed on early in their careers; they were still toiling away at retirement. The work was slow, sometimes frustrating and decidedly low-tech: Typewriters. Mimeograph machines. And index cards. Eventually, nearly 2 million of them.

And now, 90 years later, a finale. The Chicago Assyrian Dictionary is now officially complete β€” 21 volumes of Akkadian, a Semitic language (with several dialects, including Assyrian) that endured for 2,500 years. The project is more encyclopedia than glossary, offering a window into the ancient society of Mesopotamia, now modern-day Iraq, through every conceivable form of writing: love letters, recipes, tax records, medical prescriptions, astronomical observations, religious texts, contracts, epics, poems and more.

This is an amazing project. It’s not just the language at a certain point, it is the language, in context, over 1000s of years. To put that into perspective, you’d have a tough time with Middle English, much less Old English. Now imagine that that you were just “discovering” this range language from a collection of badly damaged texts.

Again, amazing work.

The Chomsky School of Language

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Noam Chomsky is a lot of things: cognitive scientist, philosopher, political activist and one of the fathers of modern linguistics, just to name a few. He has written more than 100 books and given lectures all over the world on topics ranging from syntax to failed states. In the infographic below, we take a look at some of his most well-known theories on language acquisition as if he were presenting them himself.


Via: Voxy Blog

This is a neat infographic. The original site has some lesson ideas for university classrooms. I so often forget about Chomsky, which is insane considering his influence in the field of linguistics. It’s good to have a reminder now and again.

MIT Scientist Captures 90,000 Hours of Video of His Son’s First Words, Graphs It | Fast Company

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In a talk soon to grab several million views on TED.com, cognitive scientist Deb Roy Wednesday shared a remarkable experiment that hearkens back to an earlier era of science using brand-new technology. From the day he and his wife brought their son home five years ago, the family’s every movement and word was captured and tracked with a series of fisheye lenses in every room in their house. The purpose was to understand how we learn language, in context, through the words we hear.

This could be amazing. I’d love to see a write-up and the TED Talk. It’s not up yet πŸ™

EDIT – The video was published (see below).  I’m not as excited about the talk as I thought I would be. Over have of it is essentially an advertisement for his new company focusing on social media analysis. However, I hope that he publishes (or someone associated with the group does so) findings of words, locations, interlocutors, and such.  Like many of the commenters are suggesting, this doesn’t seems to provide anything new theoretically; however, it can help to support (or weaken) these existing theories considering there has never been as complete (and unobtrusive) collection of data of this kind ever.

 

Patricia Kuhl: The linguistic genius of babies

via ted.com

Great video and new data on morpheme recognition (distinction) in infants. This is not a new idea. This has been rather well known for years, but the new technology allows for better measurement of this phenomenon. In short, babies are excellent at recognizing and distinguishing sounds from any language, given exposure, up until around 6-8 months. This ability falls off later.

Given the brevity of the presentation, I can’t criticize her too much, but her description of the critical period and what it means to learn a language is certainly not complete. In fact, from what we see here, it is downright misinformed. Her comment that no scientist doubts that a critical period exists (as presented on the chart) is absolutely wrong. In reality, many do.

She is talking almost entirely about sound recognition and distinction, but she uses an SLA theory on language that involves so much more. It’s always difficult to mix-in theories from different fields without operationalizing your terms. I’m going to guess that’s where the 10-minute time limit is restricting.

Pronouncing brotherhood (via @hanbae) – dialect problems cause adjustment issues for North Korean defectors

Check out this website I found at joongangdaily.joins.com

Thanks to @10_Magazine @holterbarbour @a_ahmad and @hanbae for this resource and their discussion of it on Twitter.

I’ve heard about this problem for a long time and it’s good to have some examples of the differences.

It’s common to hear Seoulites talk/complain about dialect distinctions that, not just with North Koreans but in those from other Provences as well. I’ve long held that Koreans in general, but Seoulites in particular, have very difficult time with language variance.

There are many reasons why this might exist, if it does. One of my theories is that Koreans have not had to deal with foreigners learning and using their language in the same way that Americans, for example, have. This may be true for Americans in more isolated areas, but in large urban areas you are likely to hear/interact with non-native English speakers every day. This has resulted in better coping mechanisms for language variation.

This is purely anecdotal, but a good deal of experience in both places leads me to believe this might be true. This is not to say that all Americans are better with language variation than Koreans, but I do suggest that this is likely a cognitive skill that is developed more in areas that see more variation.

The Unrecognized Death of Speech Recognition – shouldn’t my computer be able to understand me by now?

 Mispredicted Words, Mispredicted Futures

The accuracy of computer speech recognition flat-lined in 2001, before reaching human levels. The funding plug was pulled, but no funeral, no text-to-speech eulogy followed. Words never meant very much to computersβ€”which made them ten times more error-prone than humans. Humans expected that computer understanding of language would lead to artificially intelligent machines, inevitably and quickly. But the mispredicted words of speech recognition have rewritten that narrative. We just haven’t recognized it yet.

After a long gestation period in academia, speech recognition bore twins in 1982: the suggestively-named Kurzweil Applied Intelligence and sibling rival Dragon Systems. Kurzweil’s software, by age three, could understand all of a thousand wordsβ€”but only when spoken one painstakingly-articulated word at a time. Two years later, in 1987, the computer’s lexicon reached 20,000 words, entering the realm of human vocabularies which range from 10,000 to 150,000 words. But recognition accuracy was horrific: 90% wrong in 1993. Another two years, however, and the error rate pushed below 50%. More importantly, Dragon Systems unveiled its Naturally Speaking software in 1997 which recognized normal human speech. Years of talking to the computer like a speech therapist seemingly paid off.

However, the core language machinery that crushed sounds into words actually dated to the 1950s and β€˜60s and had not changed. Progress mainly came from freakishly faster computers and a burgeoning profusion of digital text.

Great blog post (long) on speech recognition and the lack of progress experienced in recent years. He makes a great argument. However, you must check out the comments as there are many excellent responses that counter his arguments and some responses from him to those responses.

On Language – Learning Language in Chunks

Chunking

I wondered how much β€” or how little β€” his grasp of basic linguistic etiquette is grounded in the syntactical rules that structure how words are combined in English. An idiom like β€œMake yourself at home” is rather tricky if you stop to think about it: the imperative verb β€œmake” is followed by a second-person reflexive pronoun (β€œyourself”) and an adverbial phrase (β€œat home”), but it’s difficult to break the phrase into its components. Instead, we grasp the whole thing at once.

Ritualized moments of everyday communication β€” greeting someone, answering a telephone call, wishing someone a happy birthday β€” are full of these canned phrases that we learn to perform with rote precision at an early age. Words work as social lubricants in such situations, and a language learner like Blake is primarily getting a handle on the pragmatics of set phrases in English, or how they create concrete effects in real-life interactions. The abstract rules of sentence structure are secondary.

In recent decades, the study of language acquisition and instruction has increasingly focused on β€œchunking”: how children learn language not so much on a word-by-word basis but in larger β€œlexical chunks” or meaningful strings of words that are committed to memory. Chunks may consist of fixed idioms or conventional speech routines, but they can also simply be combinations of words that appear together frequently, in patterns that are known as β€œcollocations.” In the 1960s, the linguist Michael Halliday pointed out that we tend to talk of β€œstrong tea” instead of β€œpowerful tea,” even though the phrases make equal sense. Rain, on the other hand, is much more likely to be described as β€œheavy” than β€œstrong.”

First, the They Might Be Giants children songs the author talks about will soon be in my collection. I’d never heard of them before.

Second, I’m a big believer in chunking. Interest and research findings ebb and wane in this area quite regularly. Regardless, of contrarian findings on the pedagogical focus of chunking, I think it is essential for the improvement of fluency and is a good approach to vocabulary learning.

Also, his suggestion that corpus-based findings will drive language learning materials for the near future is right on. Why wouldn’t it. One can argue about the corpra being used, but not with the approach. Don’t learn the language though up in the author’s mind. Learn language that is being used for non-learning purposes (authentic materials).

Nice to see this piece in the NYT.

Babel’s Dawn: Is Anything Universal in Language?

The question at hand: do the things that all languages have in common reflect certain universals of human thought and experience, or do they reflect the workings of a universal language faculty? Fifty years ago a third answer dominated: languages are learned from scratch and have no universals. That position, however, is still so out of favor that it is not much proposed in the current quarrel.

The latest dispute arises from a stark denial that languages have any peculiar grammatical universals of their own. It amounts to a total rejection of Chomsky’s core idea that the syntax of any individual language reflects an instance of a universal grammar (UG).Β  Nicholas Evans and Stephen C. Levinson have published a paper in the wonderful journal Behavioral and Brain Sciences, β€œThe Myth of Language Universals: Language diversity and its importance for cognitive science” (uncorrected final draft available here). Also published with the paper were a series of responses including many sharp retorts from generative grammarians who still firmly believe in UG. They score their points, but the fact that the issue has returned underlines the basic fact: after fifty years of proclaiming the existence of a UG, we still don’t know what it is. All in all the paper and responses make for a brutal slugfest.

This is a great post, not just for it’s overview and discussion of the topic, but also for pointing to such a great discussion. I’ve always regretted not reading up more on UG and criticisms, beyond basic linguistic courses. This could be a good start to get back in the game πŸ™‚

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