In the last 40 years, research on models of spoken and written language has
been split between two seemingly irreconcilable traditions: formal linguis
tics in the Chomsky tradition, and information theory in the Shannon tradit
ion. Zellig Harris had advocated a close alliance between grammatical and i
nformation-theoretic principles in the analysis of natural language, and ea
rly formal-language theory provided another strong link between information
theory and linguistics. Nevertheless, in most research on language and com
putation, grammatical and information-theoretic approaches had moved far ap
art.
Today, after many years on the defensive, the information-theoretic approac
h has gained new strength and achieved practical successes in speech recogn
ition, information retrieval, and, increasingly, in language analysis and m
achine translation. The exponential increase in the speed and storage capac
ity of computers is the proximate cause of these engineering successes, all
owing the automatic estimation of the parameters of probabilistic models of
language by counting occurrences of linguistic events in very large bodies
of text and speech. However, I will argue that information-theoretic and c
omputational ideas are also playing an increasing role in the scientific un
derstanding of language, and will help bring together formal-linguistic and
information-theoretic perspectives.