Abstract: Computational models of infant word segmentation have not been tested on a wide range of languages. This paper applies a phonotactic segmentation model to Korean. In contrast to the undersegmentation pattern previously found in English and Russian, the model exhibited more oversegmentation errors and more errors overall. Despite the high error rate, analysis suggested that lexical acquisition might not be problematic, provided that infants attend only to frequently segmented items.
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