Brianddrpm's Favorite Links on language from Diigo

LSA: About Linguistics

Tue, 24 Jun 2008 22:54:24 -0000

Highlights and Sticky Notes:

The LSA publishes a series of educational and authoritative pamphlets on language-related issues. Written with the layperson in mind, FAQs have been used as instructional aids in Linguistics courses, at information sessions for undergraduates and prospective majors interested in linguistics courses, and as part of outreach program to professionals in other fields. Click on a title below to view a FAQ on-line or to download a pdf version.

Tags: lsa linguistics language cognitive

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MIT World » : The Computational Nature of Language Learning

Mon, 02 Jun 2008 01:13:58 -0000

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Niyogi believes that an “evolutionary trajectory” links how acquisition happens at an individual level, and how variation in language springs up from one generation to the next. But rather than inheriting the grammar of your parents, you have to learn it. Examining language variation over time as if it were genetic variation, “you get a different mathematical structure…and probabilities start playing an important role.” Small differences “can have very subtle consequences giving rise to bifurcation in nonlinear dynamics of evolution.” For instance, 1000 years ago, the English were speaking a language that’s unrecognizable to us today. How has it come to be that “we have moved so far from that point through learning which is mimicking the previous generation?”

Niyogi explains that within a single population two varying languages may be in competition (say, a German and an English-type grammar). While a majority may speak the dominant variant, some children will likely be exposed to a mixture of the two. There’s a “drift” in language use, “and suddenly, what was stable becomes unstable.”

Past posts in my blog also dealt with the evolution of language. I am wondering how this plays out in larger organizational and social systems and the interaction of different systems ie Americans in Iraq or other situations. Especially with the web accelerating communications even if it is not directly connected to everybody within a system.

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Tags: decisionsystem language psychology science mit

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MIT World » : Machine Learning of Language from Distributional Evidence

Mon, 02 Jun 2008 01:13:41 -0000

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Christopher Manning thinks linguistics went astray in the 20th century when it searched “for homogeneity in language, under the misguided assumption that only homogeneous systems can be structured.” In the face of human creativity with language, rigid categories of linguistic use just don’t help explain how people actually talk and what they choose to say. For every hard and fast rule linguists find, other linguists can determine an exception. Categorical constraints rise, then come crashing down.

Tags: decisionsystem language psychology science mit

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Cognitive Daily: Study finds some thoughts really do require language

Sat, 31 May 2008 16:10:29 -0000

Some research suggests that understanding the thoughts of others -- having a theory of mind -- is one such process. Many children who are late in learning language are also late in developing a theory of mind. This story illustrates the classic theory of mind test:

Highlights and Sticky Notes:

Some research suggests that understanding the thoughts of others -- having a theory of mind -- is one such process. Many children who are late in learning language are also late in developing a theory of mind. This story illustrates the classic theory of mind test:

Very young children will say box B, because that's where the cheese is now. But at around age 4, they'll correctly answer box A, since Mouse has no way of knowing that Cat moved the cheese. Older children have successfully developed an important aspect of theory of mind -- they understand that Mouse falsely believes the cheese is in box A. But does understanding false beliefs of others require language?

When the test was a true belief test, viewers were accurate, whether they were being distracted by the rhythm or the language activity. But viewers who watched the false-belief video while repeating words successfully completed the false-belief task less than half the time. People who repeated rhythms instead of words were nearly as accurate on the false belief task as they were on the true belief task -- indeed, there was no significant difference in their performance on the two tests, and they were significantly more accurate than those distracted by the language task.

So repeating words disrupts the false-belief test, not the true-belief test, while repeating rhythm disrupts neither test. Newton and de Villiers say there are a number of aspects of language processing that could be responsible for interfering with the false-belief test, but it's quite clear that some sort of language processing is necessary in order to reason about false beliefs. So while language isn't a requirement for all thought, it most definitely appears to be a requirement for some thought.

Tags: language mind psychology brain linguistics

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Does your brain have a mind of its own? - Los Angeles Times

Sat, 31 May 2008 15:33:48 -0000

How many times has this happened to you? You leave work, decide that you need to get groceries on the way home, take a cellphone call and forget all about your plan. Next thing you know, you've driven home and forgotten all about the groceries.

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What gives? Why are we as a species so often so desperately poor at achieving our goals? If we are, as the selfish-gene theory would have it, organisms that exist only to serve the interests of our genes, why do we waste so much of our time doing things that are not, in any obvious way, remotely in the interest of our genes? How can one explain, for example, why a busy undergraduate would spend four weeks playing "Halo 3" rather than studying for his exams?

Gary Marcus, a professor of psychology at New York University, is the author, most recently, of "Kluge: The Haphazard Construction of the Human Mind."

Our conscious, deliberate systems will never have total control, and our memories will never be perfect, but as they say in Alcoholics Anonymous, recognition is the first step. If we come to recognize our limitations, and how they evolved, we just might be able to outwit our inner kluge.

Gary Marcus, a professor of psychology at New York University, is the author, most recently, of "Kluge: The Haphazard Construction of the Human Mind."

In practical terms, that means that evolution's products aren't always particularly sound. Truly dismal solutions are quickly weeded out; if someone has a genetic condition that brings them into the world without a functioning heart, they don't live long enough to reproduce. But merely adequate solutions (what engineers call "kluges") -- like the awkward, injury-prone human spine, good enough but far from perfect -- can stick around indefinitely if better solutions are too far away on the evolutionary landscape.

Still, all is not lost. Even though our short-term desires are pretty good at grabbing the steering wheel of our consciousness, our more recently evolved deliberate minds are powerful enough to regain at least some measure of control.

The problem is that evolution failed to realize that remembering goals is not like recognizing objects. When your brain sees a lion, the thing to do is to decide, lickety-split, to get out of the way. Run first; ask questions later. We're programmed for just that kind of split-second decision; just about every creature on the planet is built such that it can identify things like predators and prey very rapidly. We're not programmed to remember precise episodes from the past. Why not? Because remembering the exact date on which you last saw a lion is not particularly helpful when you're trying to get out of the way.

Tags: brain psychology evolution language mind

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MIT World » : Explorations in Language Learnability Using Probabilistic Grammars and Child-directed Speech

Mon, 25 Feb 2008 04:30:02 -0000

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How do kids manage to figure out that the word “dog” applies to a whole category of animals, not just one creature? Joshua Tenenbaum wants to understand how children and adults manage to solve such classic problems of induction. Throughout cognition, wherever you look, he says “we see places where we know more than we have a reasonable right to know about the world, places where we come to abstractions, generalizations, models of the world that go beyond our sparse, noisy, limited experience.” Tenenbaum’s goal is to come up with “general purpose computational tools for understanding how people solve these problems so successfully.”

Tags: brain decisionsystem language mit

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MIT World » : Human Simulations of Language Learning

Sun, 24 Feb 2008 23:14:22 -0000

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This workshop, explains Michael Coen, is an effort to engender temperate, collaborative discussion of a matter that inspires hot dispute: whether machine learning helps explain how humans acquire language. In particular, says Coen, machine learning advocates believe they have evidence against Noam Chomsky’s “poverty of stimulus argument,” which in essence states that language is built into us, that “children don’t receive enough linguistic inputs to explain linguistic outputs.”

Tags: decisionsystem language mit psychology science

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LIDS: Laboratory for Information and Decision Systems

Sun, 24 Feb 2008 23:00:14 -0000

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Tags: decisionsystem language mit psychology

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Visuwords online graphical dictionary and thesaurus

Sat, 15 Dec 2007 21:59:42 -0000

Tags: arts business dictionary language productivity

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