A method is described by which a rhetorical-structure tree can be realized by a text structure made up of sections, paragraphs, sentences, vertical lists, and other textual patterns, with discourse connectives added (in the correct positions) to mark rhetorical relations. We show that text-structuring can be formulated as a Constraint Satisfaction Problem , so that all solutions respecting cons...

The Text2Dialogue (T2D) system that we are developing allows digital content creators to generate attractive multi-modal dialogues presented by two virtual agents—by simply providing textual information as input. We use Rhetorical Structure Theory (RST) to decompose text into segments and to identify rhetorical discourse relations between them. These are then “acted out” by two 3D agents using ...

The AlethGen tool has been used to build a system for automatically generating replies to complaints, for a European mail-order company. In the current version, letters are generated in French. AlethGen consists of several modules: the text deep structure planner (or conceptual planner), the text surface structure planner (or rhetorical planner), the computation of pronouns and quantifiers, and...

We propose an extractive summarization system with a novel non-generative probabilistic framework for speech summarization. One of the most under-utilized features in extractive summarization is rhetorical information -semantically cohesive units that are hidden in spoken documents. We propose Rhetorical-State Hidden Markov Models (RSHMMs) to automatically decode this underlying structure in sp...

We propose an extractive summarization system with a novel non-generative probabilistic framework for speech summarization. One of the most under-utilized features in extractive summarization is rhetorical information -semantically cohesive units that are hidden in spoken documents. We propose Rhetorical-State Hidden Markov Models (RSHMMs) to automatically decode this underlying structure in sp...

This paper explores the use of a simple and computational optimality theoretic pragmatics (OT pragmatics, OTP) to the analysis of the rhetorical structure of texts. It introduces this variant of OTP briefly and then shows that it can be applied to explain coherence, rhetorical relations, discourse trees and context dependence using the occasional extra premiss. It thereby improves on existing a...

Document-level sentiment analysis is among the most popular research fields of nature language processing in recent years, in which one of major challenges is that discourse structural information can be hardly captured by existing approaches. In this paper, a domain-independent framework for documentlevel sentiment classification with weighting rules based on Rhetorical Structure Theory is pro...

Summarization involves finding the most important information in a text in order to convey the meaning of the document. In this paper, I present a method for using topic information to influence which content is selected for a summary. Texts are divided into topics using rhetorical information that creates a partition of a text into a sequence of non-overlapping topics. To investigate the effec...

generation is, like Machine Translation, one of the ultimate goal of Natural Language Processing. However, since conventional word–frequency– based abstract generation systems(e.g. [Kuhn 58]) are lacking in inter-sentential or discourse-structural analysis, they are liable to generate incoherent abstracts. On the other hand, conventional knowledge or script–based abstract generation systems(e.g...

In this paper we investigate how discourse structure a ects the meanings of words and how the meanings of words a ect discourse structure We integrate three ingredients a theory of discourse structure called sdrt which represents discourse in terms of rhetorical relations that glue together the propositions introduced by the text segments an accom panying theory of discourse attachment called d...