This research employs free model that uses only sentential features without paragraph context to extract topic sentences of a paragraph. For finding optimal combination of features, corpus-based classification is used for constructing a sentence classifier as the model. The sentence classifier is trained by using Support Vector Machine (SVM). The experiment shows that position and meta-discours...

Although the language we encounter is typically embedded in rich discourse contexts, existing models of sentence processing focus largely on phenomena that occur sentence internally. Here we analyze a video corpus of child-caregiver interactions with the aim of characterizing how discourse structure is reflected in child-directed speech and in children’s and caregivers’ behavior. We use topic c...

automated feedback that helps them revise their work and ultimately improve their writing skills. These applications also address educational researchers’ interest in individualized instruction. Specifically, feedback that refers explicitly to students’own writing is more effective than general feedback.3 Our discourse analysis software, which is embedded in Criterion (www.etstechnologies.com),...

____________________ It has been more than thirty years since Richard Braddock published the notable article in which he examined the manner that professional writers utilize topic sentences. He found in his corpus that expository paragraphs seldom began with topic sentences. Consequently, Braddock (1974) admonished teachers to stop instructing their students that most professional writers begi...

The purpose of this paper is to identify e ective factors for selecting discourse organization cue phrases in instruction dialogue that signal changes in discourse structure such as topic shifts and attentional state changes. By using a machine learning technique, a variety of features concerning discourse structure, task structure, and dialogue context are examined in terms of their e ectivene...

Modern solutions for implicit discourse relation recognition largely build universal models to classify all of the different types of discourse relations. In contrast to such learning models, we build our model from first principles, analyzing the linguistic properties of the individual top-level Penn Discourse Treebank (PDTB) styled implicit discourse relations: Comparison, Contingency and Exp...

Goals The principal objective of this project is to develop a system for representing and reasoning about the discourse context in extended man-machine dialogs. Current focus areas include the development of a general theory of multiagent planning to account for the structure of natural-langnage dialog, the development of a general knowledge representation for capturing a wide range of natura l...

In this paper, we describe an intervention for children with social and communication deficits, such as autism, based on the use of a virtual peer that can engage in tightly collaborative narrative. We present a study in which children with autism engage in collaborative narrative with both a virtual and a human peer, and the use of contingent discourse is compared. Our findings suggest that co...

This paper describes a 3-level manual discourse coding scheme that we have devised for manual tagging of the CallHome Spanish (CHS) and CallFriend Spanish (CFS) databases used in the CLARITY project. The goal of CLARITY is to explore the use of discourse structure in understanding conversational speech. The project combines empirical methods for dialogue processing with state-of-the art LVCSR (...

Deliberative, argumentative discourse is an important component of opinion formation, belief revision, and knowledge discovery; it is a cornerstone of modern civil society. Argumentation is productively studied in branches ranging from theoretical artificial intelligence to political rhetoric, but empirical analysis has suffered from a lack of freely available, unscripted argumentative dialogs....