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一失一得:通过去学习来学习音韵形态学。

One Cue's Loss Is Another Cue's Gain-Learning Morphophonology Through Unlearning.

机构信息

Institute for Linguistics, Heinrich-Heine University Düsseldorf.

Department of Linguistics, University of Oregon.

出版信息

Cogn Sci. 2024 May;48(5):e13450. doi: 10.1111/cogs.13450.

Abstract

A word often expresses many different morphological functions. Which part of a word contributes to which part of the overall meaning is not always clear, which raises the question as to how such functions are learned. While linguistic studies tacitly assume the co-occurrence of cues and outcomes to suffice in learning these functions (Baer-Henney, Kügler, & van de Vijver, 2015; Baer-Henney & van de Vijver, 2012), error-driven learning suggests that contingency rather than contiguity is crucial (Nixon, 2020; Ramscar, Yarlett, Dye, Denny, & Thorpe, 2010). In error-driven learning, cues gain association strength if they predict a certain outcome, and they lose strength if the outcome is absent. This reduction of association strength is called unlearning. So far, it is unclear if such unlearning has consequences for cue-outcome associations beyond the ones that get reduced. To test for such consequences of unlearning, we taught participants morphophonological patterns in an artificial language learning experiment. In one block, the cues to two morphological outcomes-plural and diminutive-co-occurred within the same word forms. In another block, a single cue to only one of these two outcomes was presented in a different set of word forms. We wanted to find out, if participants unlearn this cue's association with the outcome that is not predicted by the cue alone, and if this allows the absent cue to be associated with the absent outcome. Our results show that if unlearning was possible, participants learned that the absent cue predicts the absent outcome better than if no unlearning was possible. This effect was stronger if the unlearned cue was more salient. This shows that unlearning takes place even if no alternative cues to an absent outcome are provided, which highlights that learners take both positive and negative evidence into account-as predicted by domain general error-driven learning.

摘要

一个词常常表达许多不同的形态功能。一个词的哪一部分有助于整体意义的哪一部分并不总是很清楚,这就提出了这样的功能是如何学习的问题。虽然语言研究默认地假设线索和结果的共同出现足以学习这些功能(Baer-Henney、Kügler 和 van de Vijver,2015;Baer-Henney 和 van de Vijver,2012),但错误驱动的学习表明,连续性而不是毗邻性是至关重要的(Nixon,2020;Ramscar、Yarlett、Dye、Denny 和 Thorpe,2010)。在错误驱动的学习中,如果线索预测了某个结果,那么它们就会获得关联强度,如果结果不存在,那么它们就会失去强度。这种关联强度的降低被称为遗忘。到目前为止,还不清楚这种遗忘是否会对线索-结果关联产生除了被减少的关联之外的影响。为了检验遗忘的这种后果,我们在一项人工语言学习实验中教授了参与者形态音韵模式。在一个块中,两个形态结果(复数和 diminutive)的线索出现在同一个词形中。在另一个块中,一个单独的线索出现在一个不同的词形集合中,只呈现了这两个结果中的一个。我们想知道,如果参与者遗忘了这个线索与该线索单独预测的结果的关联,以及这是否允许缺席的线索与缺席的结果相关联。我们的结果表明,如果遗忘是可能的,那么参与者会发现缺席的线索更好地预测缺席的结果,而不是如果没有遗忘的话。如果被遗忘的线索更突出,这种效果会更强。这表明,即使没有提供缺席结果的替代线索,遗忘也会发生,这突出表明学习者会考虑到正、负证据,这与一般领域的错误驱动学习的预测一致。

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