  Speakers often face choices as to how to structure their intended message
into an utterance. Here we investigate the influence of contextual
predictability on the encoding of linguistic content manifested by speaker
choice in a classifier language. In English, a numeral modifies a noun directly
(e.g., three computers). In classifier languages such as Mandarin Chinese, it
is obligatory to use a classifier (CL) with the numeral and the noun (e.g.,
three CL.machinery computer, three CL.general computer). While different nouns
are compatible with different specific classifiers, there is a general
classifier "ge" (CL.general) that can be used with most nouns. When the
upcoming noun is less predictable, the use of a more specific classifier would
reduce surprisal at the noun thus potentially facilitate comprehension
(predicted by Uniform Information Density, Levy & Jaeger, 2007), but the use of
that more specific classifier may be dispreferred from a production standpoint
if accessing the general classifier is always available (predicted by
Availability-Based Production; Bock, 1987; Ferreira & Dell, 2000). Here we use
a picture-naming experiment showing that Availability-Based Production predicts
speakers' real-time choices of Mandarin classifiers.
