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  1. Computational Interpretations of the Gricean Maxims in the Generation of Referring Expressions.Robert Dale & Ehud Reiter - 1995 - Cognitive Science 19 (2):233-263.
    We examine the problem of generating definite noun phrases that are appropriate referring expressions; that is, noun phrases that (a) successfully identify the intended referent to the hearer whilst (b) not conveying to him or her any false conversational implicatures (Grice, 1975). We review several possible computational interpretations of the conversational implicature maxims, with different computational costs, and argue that the simplest may be the best, because it seems to be closest to what human speakers do. We describe our recommended (...)
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  • The Effect of Scene Variation on the Redundant Use of Color in Definite Reference.Ruud Koolen, Martijn Goudbeek & Emiel Krahmer - 2013 - Cognitive Science 37 (2):395-411.
    This study investigates to what extent the amount of variation in a visual scene causes speakers to mention the attribute color in their definite target descriptions, focusing on scenes in which this attribute is not needed for identification of the target. The results of our three experiments show that speakers are more likely to redundantly include a color attribute when the scene variation is high as compared with when this variation is low (even if this leads to overspecified descriptions). We (...)
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  • Overspecification of color, pattern, and size: salience, absoluteness, and consistency.Sammie Tarenskeen, Mirjam Broersma & Bart Geurts - 2015 - Frontiers in Psychology 6.
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  • Color categories and color appearance.Michael A. Webster & Paul Kay - 2012 - Cognition 122 (3):375-392.
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  • (1 other version)Generation of Referring Expressions: Assessing the Incremental Algorithm.Kees van Deemter, Albert Gatt, Ielka van der Sluis & Richard Power - 2012 - Cognitive Science 36 (5):799-836.
    A substantial amount of recent work in natural language generation has focused on the generation of ‘‘one-shot’’ referring expressions whose only aim is to identify a target referent. Dale and Reiter's Incremental Algorithm (IA) is often thought to be the best algorithm for maximizing the similarity to referring expressions produced by people. We test this hypothesis by eliciting referring expressions from human subjects and computing the similarity between the expressions elicited and the ones generated by algorithms. It turns out that (...)
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  • (1 other version)Generation of Referring Expressions: Assessing the Incremental Algorithm.Kees van Deemter, Albert Gatt, Ielka van der Sluis & Richard Power - 2012 - Cognitive Science 36 (5):799-836.
    A substantial amount of recent work in natural language generation has focused on the generation of ‘‘one‐shot’’ referring expressions whose only aim is to identify a target referent. Dale and Reiter's Incremental Algorithm (IA) is often thought to be the best algorithm for maximizing the similarity to referring expressions produced by people. We test this hypothesis by eliciting referring expressions from human subjects and computing the similarity between the expressions elicited and the ones generated by algorithms. It turns out that (...)
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