National Brain Research Centre, NH-8, Nainwal Mode, Manesar 122050, India.
Behav Brain Sci. 2012 Oct;35(5):302-3. doi: 10.1017/S0140525X12000313. Epub 2012 Aug 29.
We applaud Ram Frost for highlighting the need for multicultural perspectives while developing universal models of visual word recognition. We second Frost's proposal that factors like lexical morphology should be incorporated besides purely orthographic features in modeling word recognition. In support, we provide fresh evidence from Hindi (written in Devanagari), an example of hitherto under-represented alphasyllabic orthographies, in which flexible encoding of aksara (character) position is constrained by the morphological structure of words.
我们赞赏 Ram Frost 强调在开发通用视觉单词识别模型时需要多元文化视角。我们赞同 Frost 的建议，即在建模单词识别时，除了纯粹的正字法特征外，还应纳入词汇形态等因素。为此，我们提供了来自印地语（用天城文书写）的新证据，印地语是迄今为止代表性不足的全音节正字法的一个例子，其中 aksara（字符）位置的灵活编码受到单词的形态结构的限制。
