Department of Psychology, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA, 15213-3890, USA.
Psychon Bull Rev. 2022 Oct;29(5):1673-1702. doi: 10.3758/s13423-022-02086-0. Epub 2022 May 20.
The morphological structure of complex words impacts how they are processed during visual word recognition. This impact varies over the course of reading acquisition and for different languages and writing systems. Many theories of morphological processing rely on a decomposition mechanism, in which words are decomposed into explicit representations of their constituent morphemes. In distributed accounts, in contrast, morphological sensitivity arises from the tuning of finer-grained representations to useful statistical regularities in the form-to-meaning mapping, without the need for explicit morpheme representations. In this theoretically guided review, we summarize research into the mechanisms of morphological processing, and discuss findings within the context of decomposition and distributed accounts. Although many findings fit within a decomposition model of morphological processing, we suggest that the full range of results is more naturally explained by a distributed approach, and discuss additional benefits of adopting this perspective.
复合词的形态结构会影响它们在视觉词汇识别过程中的处理方式。这种影响在阅读习得过程中以及不同的语言和书写系统中有所不同。许多形态处理理论都依赖于分解机制,即把单词分解成其组成语素的显式表示。相比之下,在分布式描述中,形态敏感性是由于更细粒度的表示对形式到意义映射中的有用统计规律进行调整而产生的,而不需要显式的语素表示。在这一理论指导的综述中,我们总结了形态处理机制的研究,并在分解和分布式描述的背景下讨论了研究结果。尽管许多发现都符合形态处理的分解模型,但我们认为,更自然的解释是采用分布式方法,并且讨论了采用这种观点的额外好处。