对 800 张包含 200 件物品的英文照片进行图片命名计时。

IF 5.4 3区 材料科学 Q2 CHEMISTRY, PHYSICAL ACS Applied Energy Materials Pub Date : 2024-10-01 Epub Date: 2024-03-19 DOI:10.3758/s13428-024-02380-w
Rens van Hoef, Dermot Lynott, Louise Connell
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引用次数: 0

摘要

本研究介绍了 800 张高质量照片的图片命名规范,这些照片包含 200 个自然物体和人工制品类别,每个物体有四张独特的图片。我们要求参与者为看到的每张图片提供一个最合适的名称。我们报告了每张图片的识别延迟以及所提供名称的几个标准变量:一致度、H 统计量(即命名不确定性水平)、Zipf 词频和词长。对识别潜伏期的分析表明,重要的是要考虑参与者可能赋予每个图像对象的标签的多样性,而不是简单地关注每个图像的单一名称(即模式名称或最常见的名称)。因此,规范提供了每幅图像的候选标签列表,并对每幅图像的词长和词频进行了加权测量,其中包含了所有提供的名称,以及仅基于最常见名称的模态测量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Timed picture naming norms for 800 photographs of 200 objects in English.

The present study presents picture-naming norms for a large set of 800 high-quality photographs of 200 natural objects and artefacts spanning a range of categories, with four unique images per object. Participants were asked to provide a single, most appropriate name for each image seen. We report recognition latencies for each image, and several normed variables for the provided names: agreement, H-statistic (i.e. level of naming uncertainty), Zipf word frequency and word length. Rather than simply focusing on a single name per image (i.e. the modal or most common name), analysis of recognition latencies showed that it is important to consider the diversity of labels that participants may ascribe to each pictured object. The norms therefore provide a list of candidate labels per image with weighted measures of word length and frequency per image that incorporate all provided names, as well as modal measures based on the most common name only.

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来源期刊
ACS Applied Energy Materials
ACS Applied Energy Materials Materials Science-Materials Chemistry
CiteScore
10.30
自引率
6.20%
发文量
1368
期刊介绍: ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.
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