Ambridge Ben, Blything Ryan P
University of Liverpool,ESRC International Centre for Language and Communicative Development (LuCiD).
University of Manchester.
J Child Lang. 2016 Nov;43(6):1245-76. doi: 10.1017/S0305000915000586. Epub 2015 Nov 16.
A central question in language acquisition is how children build linguistic representations that allow them to generalize verbs from one construction to another (e.g., The boy gave a present to the girl → The boy gave the girl a present), whilst appropriately constraining those generalizations to avoid non-adultlike errors (e.g., I said no to her → *I said her no). Although a consensus is emerging that learners solve this problem using both statistical and semantics-based learning procedures (e.g., entrenchment, pre-emption, and semantic verb class formation), there currently exist few - if any - proposals for a learning model that combines these mechanisms. The present study used a connectionist model to test an account that argues for competition between constructions based on (a) verb-in construction frequency, (b) relevance of constructions for the speaker's intended message, and (c) fit between the fine-grained semantic properties of individual verbs and individual constructions. The model was able not only (a) to simulate the overall pattern of overgeneralization-then-retreat, but also (b) to use the semantics of novel verbs to predict their argument structure privileges (just as real learners do), and
语言习得中的一个核心问题是，儿童如何构建语言表征，使他们能够将动词从一种结构泛化到另一种结构（例如，男孩给女孩一件礼物→男孩给女孩一件礼物），同时适当地限制这些泛化，以避免出现非成人式的错误（例如，我对她说不→*我对她说不）。尽管越来越多的人达成共识，即学习者使用基于统计和语义的学习程序（例如，固化、优先占有和语义动词类形成）来解决这个问题，但目前几乎没有（如果有的话）关于结合这些机制的学习模型的提议。本研究使用了一个联结主义模型来测试一种观点，该观点认为基于以下因素在结构之间存在竞争：（a）动词在结构中的频率，（b）结构与说话者意图信息的相关性，以及（c）单个动词的细粒度语义属性与单个结构之间的契合度。该模型不仅能够（a）模拟过度泛化然后退缩的总体模式，而且能够（b）利用新动词的语义来预测它们的论元结构特权（就像真正的学习者一样），并且
