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1
Referring in dialogue : alignment or construction?
Viethen, Jette; Dale, Robert; Guhe, Markus. - : Routledge, 2014
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2
Generating subsequent reference in shared visual scenes : computation vs. re-use
Viethen, Jette; Dale, Robert; Guhe, Markus. - : Association for Computational Linguistics, 2011
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3
Building an audio-visual corpus of Australian English : large corpus collection with an economical portable and replicable Black Box
Burnham, Denis; Estival, Dominique; Goecke, Roland. - : International Speech Communication Association, 2011
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4
GRE3D7 : A Corpus of distinguishing descriptions for objects in visual scenes
Viethen, Jette; Dale, Robert. - : Association for Computational Linguistics (ACL), 2011
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5
The Impact of visual context on the content of referring expressions
Viethen, Jette; Dale, Robert; Guhe, Markus. - : Association for Computational Linguistics (ACL), 2011
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6
Building an audio-visual corpus of Australian English : large corpus collection with an economical portable and replicable Black Box
Burnham, Denis K. (R7357); Estival, Dominique (R16320); Fazio, Steven (R15706). - : Rundle Mall, S.A., Causal Productions, 2011
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7
Dialogue reference in a visual domain
Viethen, Jette; Zwarts, Simon; Dale, Robert. - : Valetta, Malta : European Language Resources Association, 2010
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8
Referring expression generation through attribute-based heuristics
Dale, Robert; Viethen, Jette. - : United States : Association for Computational Linguistics (ACL), 2009
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9
The Use of spatial relations in referring expression generation
Viethen, Jette; Dale, Robert. - : Association for Computational Linguistics, 2008
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10
Algorithms for generating referring expressions : do they do what people do?
Viethen, Jette; Dale, Robert. - : Stroudsburg, USA : Association for Computational Linguistics, 2006
Abstract: The natural language generation literature provides many algorithms for the generation of referring expressions. In this paper, we explore the question of whether these algorithms actually produce the kinds of expressions that people produce. We compare the output of three existing algorithms against a data set consisting of human-generated referring expressions, and identify a number of significant differences between what people do and what these algorithms do. On the basis of these observations, we suggest some ways forward that attempt to address these differences. ; 10 page(s)
Keyword: 080100 Artificial Intelligence and Image Processing
URL: http://hdl.handle.net/1959.14/102703
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