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Language acquisition and cross-modal associations: Computational simulation of the result of infant studies

机译:语言习得和跨模态协会:婴儿研究结果的计算模拟

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This paper discusses recent results obtained with a computational model of language acquisition. In previous papers, this model, developed in the ACORNS project, has shown to be able to learn word-like units from stimuli in which utterances are paired with visual information. In this paper we extend the ACORNS experiments to the case where utterances are paired with a ambiguous visual representation, as to obtain a computational correlate of the findings by Smith and Yu in 2008. Smith and Yu stipulate that a young infant is confronted with an uncertainty problem, how to pair a word, embedded in a sentence, and a referent, embedded in a rich visual scene. They show that young infants can resolve the uncertainty problem by evaluating the statistical evidence across many individually ambiguous words and scenes. We investigate to what extent the ACORNS model is able to deal with cross-modal ambiguity. Moreover, we show the positive effect of an 'active' role during learning when confronted with ambiguity, based on internal confidence.
机译:本文讨论了最近的结果,用语言习得计算模型获得。在先前的论文中,该模型在橡子项目中开发,已经表明能够从刺激中学习类似的单词,其中话语与视觉信息配对。在本文中,我们将橡子实验扩展到具有暧昧视觉表现的话语与暧昧视觉表现相配的情况,以获得史密斯和余的调查结果在2008年的计算相关。史密斯和俞规定了一个年轻的婴儿面对不确定性问题,如何将一个单词配对,嵌入在句子中,以及嵌入在丰富的视觉场景中。他们表明年轻婴儿可以通过评估在许多单独含糊的单词和场景中的统计证据来解决不确定性问题。我们调查橡子模型能够处理跨模仿歧义的程度。此外,根据内部信心,我们展示了在学习期间“积极”角色的积极影响。

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