Complexity in sign languages

Abstract

Abstract Sign languages are human communication systems that are equivalent to spoken language in their capacity for information transfer, but which use a dynamic visual signal for communication. Thus, linguistic metrics of complexity, which are typically developed for linear, symbolic linguistic representation (such as written forms of spoken languages) do not translate easily into sign language analysis. A comparison of physical signal metrics, on the other hand, is complicated by the higher dimensionality (spatial and temporal) of the sign language signal as compared to a speech signal (solely temporal). Here, we review a variety of approaches to operationalizing sign language complexity based on linguistic and physical data, and identify the approaches that allow for high fidelity modeling of the data in the visual domain, while capturing linguistically-relevant features of the sign language signal.