Competence and performance

The current generation of language processing systems is based on linguistically motivated competence models of natural languages. The problems encountered with these systems suggest the need for performance-models of language processing, which take into account the statistical properties of actual language use. This article describes the overall set-up of such a model. The system I propose employs an annotated corpus; in analysing new input it tries to find the most probable way to reconstruct this input from fragments that are already contained in the corpus. This perspective on language processing also has interesting consequences for linguistic theory