The present paper addresses the study of non-arbitrariness in language within a deep learning framework. We present a set of experiments aimed at assessing the pervasiveness of different forms of non-arbitrary phonological patterns across a set of typologically distant languages. Different sequence-processing neural networks are trained in a set…

This study has two goals. First, we present much-needed empirical linguistic data and systematic analyses on the spatial semantic systems in English and Korean, two languages that have been extensively compared to date in the debate on spatial language and spatial cognition. We conduct our linguistic investigation comprehensively, encompassing the…

This study investigated the relative contribution of perception/cognition and language-specific semantics in nonverbal categorization of spatial relations. English and Korean speakers completed a video-based similarity judgment task involving containment, support, tight fit, and loose fit. Both perception/cognition and language served as resources…