Language choice models for microplanning and readability

This paper describes the construction of language choice models for the microplanning of discourse relations in a Natural Language Generation system that attempts to generate appropriate texts for users with varying levels of literacy. The models consist of constraint satisfaction problem graphs that have been derived from the results of a corpus analysis. The corpus that the models are based on was written for good readers. We adapted the models for poor readers by allowing certain constraints to be tightened, based on psycholinguistic evidence. We describe how the design of microplanner is evolving. We discuss the compromises involved in generating more readable textual output and implications of our design for NLG architectures. Finally we describe plans for future work

Generating readable texts for readers with low basic skills

Most NLG systems generate texts for readers with good reading ability, but SkillSum adapts its output for readers with poor literacy. Evaluation with lowskilled readers confirms that SkillSum's knowledge-based microplanning choices enhance readability. We also discuss future readability improvements

THE "POWER" OF TEXT PRODUCTION ACTIVITY IN COLLABORATIVE MODELING : NINE RECOMMENDATIONS TO MAKE A COMPUTER SUPPORTED SITUATION WORK

Language is not a direct translation of a speaker’s or writer’s knowledge or intentions. Various complex processes and strategies are involved in serving the needs of the audience: planning the message, describing some features of a model and not others, organizing an argument, adapting to the knowledge of the reader, meeting linguistic constraints, etc. As a consequence, when communicating about a model, or about knowledge, there is a complex interaction between knowledge and language. In this contribution, we address the question of the role of language in modeling, in the specific case of collaboration over a distance, via electronic exchange of written textual information. What are the problems/dimensions a language user has to deal with when communicating a (mental) model? What is the relationship between the nature of the knowledge to be communicated and linguistic production? What is the relationship between representations and produced text? In what sense can interactive learning systems serve as mediators or as obstacles to these processes

Reading comprehension: nature, assessment and teaching.

The goal of reading is understanding. In order to understand print, a child must be able to decode the words on the page and to extract meaning. A large body of research focuses on how children learn to decode text and how best to foster children’s decoding skills. In contrast, we know much less about the process of reading comprehension in children. In this booklet we first consider what is required in order to ‘read for meaning’. We then move on to discuss children who have difficulties with reading comprehension. Our aim is to enable teachers to assess individual differences in reading and to foster the comprehension strategies that characterize fluent reading

Comprehensibility and the basic structures of dialogue

The study of what makes utterances difficult or easy to understand is one of the central topics of research in comprehension. It is both theoretically attractive and useful in practice. The more we know about difficulties in understanding the more we know about understanding. And the better we grasp typical problems of understanding in certain types of discourse and for certain recipients the better we can overcome these problems and the better we can advise people whose job it is to overcome such problems. It is therefore not surprising that comprehensibility has been the object of much reflection as far back as the days of classical rhetoric and that it is a center of lively interest in several present-day scientific disciplines, ranging from artificial intelligence and educational psychology to linguistics