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…