The Cognitive Complexity of Language (revisited)

It is largely from Descartes and the seventeenth century Port-Royal school of French philosophers that Noam Chomsky, by far the most influential linguist and language theoretician of the twentieth century, drew the fundamental notions that led to the establishment of linguistics as a cognitive science; or more specifically, in Chomsky's words, as "a branch of cognitive psychology". Descartes was a rationalist; he held that human beings are endowed with 'innate ideas' that determine and constrain the form of human knowledge in quite specific ways, and that it is these innate ideas that distinguish the creative intelligence of humans from the mechanical behaviour of animals and machines. Those innate ideas associated specifically with language Chomsky calls 'universal grammar', "the system of principles, conditions, and rules that are elements or properties of all human languages not merely by accident but by ... biological ... necessity" (Chomsky, 1975, p.29). It is this 'universal grammar' that accounts for the invariance of certain properties -- 'linguistic universals' -- across all languages, and for the remarkable speed with which young children acquire their own native tongue. Children learn their first language so quickly, Chomsky argues, because they in some sense already 'know' what human languages look like: they are biologically equipped with what he calls a 'Language Acquisition Device'. If such principles are indeed innate, then a compelling reason for studying human language is that it may gives us insights into the structure of the mind itself.[1]

Chomsky has drawn a distinction between linguistic competence and linguistic performance, the former being an ideal speaker-hearer's knowledge of her language, and the latter a person's actual use of language in real situations. The primary task of linguistics, in Chomsky's view, is to characterise, in the form of a grammar of the language, the ideal speaker-hearer's intrinsic competence. The emphasis in artificial intelligence approaches to natural language has been slightly different. Of course it is important to describe the formal properties of languages; but such descriptions do not, in themselves, say how you would go about producing an actual utterance, or understanding the utterances of others. Since the main thrust of natural language processing in artificial intelligence has been to design machines that can produce and understand human languages, there has been a far greater concern among cognitive scientists to give accounts of how we put to use the internalised knowledge we have of our mother tongues. This division is mirrored in the distinction cognitive scientists make between grammars and parsers, which are programs that make use of grammatical knowledge. In most computational natural language systems, the grammar of the language and the parser that works on it are written as separate and independent components -- the grammar is encoded as a declarative data structure, the parser as a procedural program.

We'll return to the topic of parsing later in this tutorial.


1
Chomsky's writings are often extremely dense and difficult. If you would like to know more about his theory of language, you could browse through the more general sections of his Cartesian Linguistics (1966), Reflections on Language (1975), and Rules and Representations (1980). A good summary of Chomsky's current thought is Raphael Salkie's book, endorsed by Chomsky himself, The Chomsky Update.