The HealthDoc project aims to provide a comprehensive approach to the customization of patient-information and health-education materials through the development of sophisticated natural language generation systems. We adopt a model of patient education that takes into account patient information ranging from simple medical data to complex cultural beliefs, so that our work provides both an impetus and testbed for research in multicultural health communication. We propose a model of language generation, `generation by selection and repair ', that relies on a `master-document' representation that pre-determines the basic form and content of a text, yet is amenable to editing and revision for customization. The implementation of this model has so far led to the design of a sentence planner that integrates multiple complex planning tasks and a rich set of ontological and linguistic knowledge sources. 1 Customizing patient-education material Present-day health-education and patient-infor...

This paper criticizes previous approaches to perlocutions and previous formalizations of perlocutionary effects of communicative actions by showing that some of their fundamental assumptions are inconsistent with data from communication studies, psychology, and social studies of persuasion. Consequently, it argues for a data-driven approach to pragmatics, one that permits pragmatic theories to be falsified and improved. Introduction Since Austin published his most influential book (1962), researchers in linguistics and artificial intelligence have analyzed, challenged, and modified to an impressive extent his initial conception of locutionary and illocutionary acts. In contrast, perlocutionary acts have received much less attention. To my knowledge, with the exception of a few endeavors that address the issue peripherally (Cohen & Perrault 1979; Allen & Perrault 1980; Perrault & Allen 1980; Cohen & Levesque 1985; Appelt 1985; Cohen & Levesque 1990; Perrault 1990), the artific...