  In this paper we propose a learning paradigm for the problem of understanding
spoken language. The basis of the work is in a formalization of the
understanding problem as a communication problem. This results in the
definition of a stochastic model of the production of speech or text starting
from the meaning of a sentence. The resulting understanding algorithm consists
in a Viterbi maximization procedure, analogous to that commonly used for
recognizing speech. The algorithm was implemented for building
