Kol Sheli, Nir Bracha, Wintner Shuly
Department of Computer Science, University of Haifa.
Department of Communication Disorders, University of Haifa.
J Child Lang. 2014 Jan;41(1):176-99. doi: 10.1017/S0305000912000694. Epub 2013 Jan 24.
Several models of language acquisition have emerged in recent years that rely on computational algorithms for simulation and evaluation. Computational models are formal and precise, and can thus provide mathematically well-motivated insights into the process of language acquisition. Such models are amenable to robust computational evaluation, using technology that was developed for Information Retrieval and Computational Linguistics. In this article we advocate the use of such technology for the evaluation of formal models of language acquisition. We focus on the Traceback Method, proposed in several recent studies as a model of early language acquisition, explaining some of the phenomena associated with children's ability to generalize previously heard utterances and generate novel ones. We present a rigorous computational evaluation that reveals some flaws in the method, and suggest directions for improving it.
近年来出现了几种语言习得模型，它们依靠计算算法进行模拟和评估。计算模型形式化且精确，因此能够为语言习得过程提供数学上有充分依据的见解。这类模型适合使用为信息检索和计算语言学开发的技术进行强大的计算评估。在本文中，我们提倡使用此类技术来评估语言习得的形式模型。我们关注在最近几项研究中提出的回溯法，它作为早期语言习得的一种模型，解释了一些与儿童概括先前听到的话语并生成新话语的能力相关的现象。我们进行了严格的计算评估，揭示了该方法中的一些缺陷，并提出了改进方向。
