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The learning of adjectives and nouns from affordance and appearance features

机译：从能力和外观特征中学习形容词和名词

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摘要

We study how a robot can link concepts represented by adjectives and nouns in language with its own sensorimotor interactions. Specifically, an iCub humanoid robot interacts with a group of objects using a repertoire of manipulation behaviors. The objects are labeled using a set of adjectives and nouns. The effects induced on the objects are labeled as affordances, and classifiers are learned to predict the affordances from the appearance of an object. We evaluate three different models for learning adjectives and nouns using features obtained from the appearance and affordances of an object, through cross-validated training as well as through testing on novel objects. The results indicate that shape-related adjectives are best learned using features related to affordances, whereas nouns are best learned using appearance features. Analysis of the feature relevancy shows that affordance features are more relevant for adjectives, and appearance features are more relevant for nouns. We show that adjective predictions can be used to solve the odd-one-out task on a number of examples. Finally, we link our results with studies from psychology, neuroscience and linguistics that point to the differences between the development and representation of adjectives and nouns in humans.
机译：我们研究了机器人如何通过其自身的感觉运动相互作用将语言中的形容词和名词所代表的概念联系起来。具体来说，iCub人形机器人使用一系列操作行为与一组对象进行交互。这些对象使用一组形容词和名词来标记。在对象上引起的影响被标记为能力，并且学习分类器以根据对象的外观预测能力。我们使用从对象的外观和承受能力获得的特征，通过交叉验证的训练以及对新颖对象的测试，评估了三种用于学习形容词和名词的模型。结果表明，与形容词相关的形容词最好是使用与能力特征相关的特征来学习，而名词是使用外观特征来最好地学习。对特征相关性的分析表明，提供特征与形容词更相关，而外观特征与名词更相关。我们证明了形容词预测可用于解决许多示例中的奇一单任务。最后，我们将研究结果与心理学，神经科学和语言学的研究联系起来，这些研究指出了形容词和名词在人类中的发展和表征之间的差异。

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  • 来源
    《Adaptive Behavior》 |2013年第6期|437-451|共15页
  • 作者

    Onur Yuerueten; Erol Sahin; Sinan Kalkan;

  • 作者单位

    Department of Computer and Communication Sciences, Ecole Polytechnique Federale de Lausanne, INR 018 (Batiment INR), Station 14 CH-1015, Lausanne, Switzerland;

    KOVAN Research Laboratory, Department of Computer Engineering, Middle East Technical University, Turkey;

    KOVAN Research Laboratory, Department of Computer Engineering, Middle East Technical University, Turkey;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    Affordances; nouns; adjectives;

    机译：负担;名词形容词;

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