Toward Cognitively Constrained Models of Language Processing: A Review
Toward Cognitively Constrained Models of Language Processing: A Review
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DOI：
10.3389/fcomm.2017.00011
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发表时间：
2017-09
影响因子：
2.4
通讯作者：
Margreet Vogelzang;Anne C. Mills;D. Reitter;Jacolien van Rij;P. Hendriks;H. van Rijn
中科院分区：
文献类型：
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作者：
Margreet Vogelzang;Anne C. Mills;D. Reitter;Jacolien van Rij;P. Hendriks;H. van Rijn
语言处理不是一种孤立的能力，而是嵌入到我们认知的其他方面。然而，语言加工在多大程度上以及如何与一般认知资源相互作用，这在很大程度上仍然是未知的。这个问题可以用认知约束的计算模型来研究，这些模型模拟了语言处理中涉及的认知过程。在认知模型中实现的理论主张与一般的架构约束（如内存限制）相互作用。通过这种方式，它生成了可以在实验中测试的新预测，从而生成了可以产生新的理论见解的新数据。这种理论-模型-实验循环是一种很有前途的方法，可以用来研究语言处理的一些方面，而这些方面是传统实验技术难以研究的。本综述具体考察了刘易斯和Vasishth（2005），Reitter，Keller和摩尔（2011），以及货车Rij，货车Rijn和Hendriks（2010）的语言处理模型，所有这些模型都是在认知架构ACT-R中实现的（安德森，博瑟尔，伯恩，道格拉斯，Lebiere和秦，2004）。这些模型都受到认知结构所提供的认知能力假设的限制，但使用不同的语言方法。正因为如此，他们的比较提供了洞察的程度上的假设一般认知资源的影响具体实施的语言能力模型。例如，人类语言处理的绝对速度和准确性是认知建模领域目前面临的挑战，因为它似乎不符合其他认知过程中发现的相同记忆和处理能力。语言处理的基于架构的认知模型可能能够明确哪些语言特定的资源需要获得和处理自然语言。这篇综述从两个角度揭示了认知约束的语言处理模型：我们讨论了1）目前采用的认知假设是否符合语言处理的要求，以及2）验证的认知架构如何约束语言动机的模型，在其他条件相同的情况下，这将增加这些模型的认知能力。总体而言，认知约束的语言处理模型的评估将允许更好地理解数据，语言理论，认知假设和解释之间的关系。
Language processing is not an isolated capacity, but is embedded in other aspects of our cognition. However, it is still largely unexplored to what extent and how language processing interacts with general cognitive resources. This question can be investigated with cognitively constrained computational models, which simulate the cognitive processes involved in language processing. The theoretical claims implemented in cognitive models interact with general architectural constraints such as memory limitations. This way, it generates new predictions that can be tested in experiments, thus generating new data that can give rise to new theoretical insights. This theory-model-experiment cycle is a promising method for investigating aspects of language processing that are difficult to investigate with more traditional experimental techniques. This review specifically examines the language processing models of Lewis and Vasishth (2005), Reitter, Keller, and Moore (2011), and Van Rij, Van Rijn, and Hendriks (2010), all implemented in the cognitive architecture ACT-R (Anderson, Bothell, Byrne, Douglass, Lebiere, & Qin, 2004). These models are all limited by the assumptions about cognitive capacities provided by the cognitive architecture, but use different linguistic approaches. Because of this, their comparison provides insight into the extent to which assumptions about general cognitive resources influence concretely implemented models of linguistic competence. For example, the sheer speed and accuracy of human language processing is a current challenge in the field of cognitive modeling, as it does not seem to adhere to the same memory and processing capacities that have been found in other cognitive processes. Architecture-based cognitive models of language processing may be able to make explicit which language-specific resources are needed to acquire and process natural language. The review sheds light on cognitively constrained models of language processing from two angles: we discuss 1) whether currently adopted cognitive assumptions meet the requirements for language processing, and 2) how validated cognitive architectures can constrain linguistically motivated models, which, all other things being equal, will increase the cognitive plausibility of these models. Overall, the evaluation of cognitively constrained models of language processing will allow for a better understanding of the relation between data, linguistic theory, cognitive assumptions, and explanation.