Reference Production as Search: The Impact of Domain Size on the Production of Distinguishing Descriptions
Reference Production as Search: The Impact of Domain Size on the Production of Distinguishing Descriptions
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DOI：
10.1111/cogs.12375
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发表时间：
2017-05-01
影响因子：
2.5
通讯作者：
van Gompel, Roger P. G.
中科院分区：
文献类型：
--
作者：
Gatt, Albert;Krahmer, Emiel;van Gompel, Roger P. G.
当在视觉语境中产生对目标指称物的描述时，说话者需要选择一组属性来将其与其干扰物区分开来。语言产生/生成的计算模型通常将其建模为搜索过程，并预测所需的时间将随着场景中干扰物的数量和区分目标所需的属性的数量而增加。这些预测让人想起视觉搜索中的经典发现;然而，与参考产生模型不同，视觉搜索模型还预测搜索在某些条件下可以变得非常有效，而参考产生模型没有考虑到这一点。本文实证研究了这些模型的预测。在两个实验中，我们表明，所花费的时间来计划一个参考expressions反映的语音启动延迟的影响，分心集的大小和所需的属性的数量，但这在很大程度上取决于所考虑的属性的可辨别性。我们讨论了目前的参考生产模型和最近的工作中的视觉搜索的作用显着的影响。
When producing a description of a target referent in a visual context, speakers need to choose a set of properties that distinguish it from its distractors. Computational models of language production/generation usually model this as a search process and predict that the time taken will increase both with the number of distractors in a scene and with the number of properties required to distinguish the target. These predictions are reminiscent of classic findings in visual search; however, unlike models of reference production, visual search models also predict that search can become very efficient under certain conditions, something that reference production models do not consider. This paper investigates the predictions of these models empirically. In two experiments, we show that the time taken to plan a referring expressionas reflected by speech onset latenciesis influenced by distractor set size and by the number of properties required, but this crucially depends on the discriminability of the properties under consideration. We discuss the implications for current models of reference production and recent work on the role of salience in visual search.