Automatic Generation of Multi-Modal Dialogue from Text Based on Discourse Structure Analysis

Prendinger, Helmut; Piwek, Paul; Ishizuka, Mitsuru

doi:10.1109/icosc.2007.4338329

Cited by 2 publications

(2 citation statements)

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“…Discourse parsing and other higher-level view of text allowing some flexibility in the choice of formal representation. This tree likes structure has been used by (piwek et al, 2007) [15] for text generation. The tree used by Daniel marcuu (2000) [6] for extracting summary from text.…”

Section: Related Workmentioning

confidence: 99%

Information Extraction Using Discourse Analysis from Newswires

Rahangdale¹,

Ramdeobaba²

2014

IJITCS

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This paper proposes Natural language based Discourse Analysis method used for extracting information from the news article of different domain. The Discourse analysis used the Rhetorical Structure theory which is used to find coherent group of text which are most prominent for extracting information from text. RST theory used the Nucleus-Satellite concept for finding most prominent text from the text document. After Discourse analysis the text analysis has been done for extracting domain related object and relates this object. For extracting the information knowledge based system has been used which consist of domain dictionary .The domain dictionary has a bag of words for domain. The system is evaluated according gold-of-art analysis and human decision for extracted information.

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Section: Related Workmentioning

confidence: 99%

Information Extraction Using Discourse Analysis from Newswires

Rahangdale¹,

Ramdeobaba²

2014

IJITCS

View full text Add to dashboard Cite

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“…However, the effort to create such content is often tremendous, and current technologies offer only insufficient or partial solutions [1]. Therefore, the problem this article aims to address is the development of an effective technology to automatically create high-quality content, so that anyone can produce professional multi-modal content easily [26].…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for Automatically Generating Multi-Modal Dialogue From Text

Prendinger

Piwek

Ishizuka

2007

Int. J. Semantic Computing

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In this article, we propose a novel method for generating engaging multi-modal content automatically from text. Rhetorical Structure Theory (RST) is used to decompose text into discourse units and to identify rhetorical discourse relations between them. Rhetorical relations are then mapped to question–answer pairs in an information preserving way, i.e., the original text and the resulting dialogue convey essentially the same meaning. Finally, the dialogue is "acted out" by two virtual agents. The network of dialogue structures automatically built up during this process, called DialogueNet, can be reused for other purposes, such as personalization or question–answering.

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Automatic Generation of Multi-Modal Dialogue from Text Based on Discourse Structure Analysis

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Cited by 2 publications

References 10 publications

Information Extraction Using Discourse Analysis from Newswires

Information Extraction Using Discourse Analysis from Newswires

A Novel Method for Automatically Generating Multi-Modal Dialogue From Text

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