Applying information theory to linguistics

Researchers believe that information theory - the discipline that gave us digital communication - can explain differences between human languages.

The majority of languages - roughly 85 per cent of them - can be sorted into two categories: those, like English, in which the basic sentence form is subject-verb-object (''the girl kicks the ball''), and those, like Japanese, in which the basic sentence form is subject-object-verb (''the girl the ball kicks'').

The reason for the difference has remained somewhat mysterious, but researchers from MIT's Department of Brain and Cognitive Sciences now believe that they can account for it using concepts borrowed from information theory, the discipline, invented almost singlehandedly by longtime MIT professor Claude Shannon, that led to the digital revolution in communications.

The researchers will present their hypothesis in an upcoming issue of the journal Psychological Science.

Shannon was largely concerned with faithful communication in the presence of ''noise'' - any external influence that can corrupt a message on its way from sender to receiver. Ted Gibson, a professor of cognitive sciences at MIT and corresponding author on the new paper, argues that human speech is an example of what Shannon called a ''noisy channel.''

''If I'm getting an idea across to you, there's noise in what I'm saying,'' Gibson says. ''I may not say what I mean - I pick up the wrong word, or whatever. Even if I say something right, you may hear the wrong thing. And then there's ambient stuff in between on the signal, which can screw us up. It's a real problem.'' In their paper, the MIT researchers argue that languages develop the word order rules they do in order to minimise the risk of miscommunication across a noisy channel.