Edward Gibson
MIT
Edward Gibson
MIT
United States
Information processing and cross-linguistic universals
Finding explanations for the observed variation in human languages is the primary goal of linguistics, and promises to shed light on the nature of human cognition. One particularly attractive set of explanations is functional in nature, holding that language universals are grounded in the known properties of human information processing. The idea is that lexicons and grammars of languages have evolved so that language users can communicate using words and sentences that are relatively easy to produce and comprehend.
In this talk, I summarize results from explorations in two linguistic domains, from an information-processing point of view. First, in the lexical domain, I show that word lengths are optimized on average according to predictability in context, as would be expected under an information theoretic analysis. I then apply a simple information theory analysis to the language for color. The number of color terms varies drastically across languages. Yet despite these differences, certain terms (e.g., red) are prevalent, which has been attributed to perceptual salience.
Our work provides evidence for an alternative hypothesis: The use of color terms depends on communicative needs. Across languages, from the hunter-gatherer Tsimane’ people of the Amazon to students in Boston, warm colors are communicated more efficiently than cool colors. This cross-linguistic pattern reflects the color statistics of the world: Objects (what we talk about) are typically warm-colored, and backgrounds are cool-colored. Communicative needs also explain why the number of color terms varies across languages: Cultures vary in how useful color is. Industrialization, which creates objects distinguishable solely based on color, increases color usefulness.
Finally, in the realm of syntax, I show that all the world’s languages that we can currently analyze minimize syntactic dependency lengths to some degree, as would be expected under information processing considerations.