ABSTRACT

Working memory (WM) is critical for many cognitive functions including language production. A key feature of WM is its capacity limitation. Two models have been proposed to account for such capacity limitation: slot models and resource models. In recent years, resource models have found support in both visual and auditory perception, but do they also extend to production? We investigate this by analyzing sublexical errors from four individuals with aphasia. Using tools from computational linguistics, we first define the concept of “precision” of sublexical errors. We then demonstrate that such precision decreases with increased working memory load, i.e., word length, as predicted by resource models. Finally, we rule out alternative accounts of this effect, such as articulatory simplification. These data provide the first evidence for the applicability of the resource model to production and further point to the generalizability of this account as a model of resource division in WM.

摘要

工作记忆 (WM) 对于包括语言生成在内的许多认知功能至关重要。WM 的一个关键特征是其容量限制。已经提出了两种模型来解决这种容量限制：时隙模型和资源模型。近年来，资源模型在视觉和听觉感知方面都得到了支持，但它们是否也扩展到生产领域？我们通过分析四名失语症患者的词汇下错误来对此进行调查。使用计算语言学的工具，我们首先定义词汇下错误的“精度”概念。然后，我们证明，正如资源模型所预测的那样，这种精度随着工作记忆负载（即字长）的增加而降低。最后，我们排除了这种效应的其他解释，例如发音简化。