Signal dimensionality and the emergence of combinatorial structure

Abstract

In language, a small number of meaningless building blocks can be combined into an unlimited set of meaningful utterances. This is known as combinatorial structure. One hypothesis for the initial emergence of combinatorial structure in language is that recombining elements of signals solves the problem of overcrowding in a signal space. Another hypothesis is that iconicity may impede the emergence of combinatorial structure. However, how these two hypotheses relate to each other is not often discussed. In this paper, we explore how signal space dimensionality relates to both overcrowding in the signal space and iconicity. We use an artificial signalling experiment to test whether a signal space and a meaning space having similar topologies will generate an iconic system and whether, when the topologies differ, the emergence of combinatorially structured signals is facilitated. In our experiments, signals are created from participants' hand movements, which are measured using an infrared sensor. We found that participants take advantage of iconic signal-meaning mappings where possible. Further, we use trajectory predictability, measures of variance, and Hidden Markov Models to measure the use of structure within the signals produced and found that when topologies do not match, then there is more evidence of combinatorial structure. The results from these experiments are interpreted in the context of the differences between the emergence of combinatorial structure in different linguistic modalities (speech and sign).

The iconicity toolbox: empirical approaches to measuring iconicity

“…However, there are also automatic ways The Iconicity Toolbox MANUSCRIPT ACCEPTED FOR PUBLICATION 21 to measure features that can serve as a proxy of iconicity. For vocal modalities, properties of auditory signals such as pitch and amplitude can be analysed in this way (Little et al, 2017b;Perlman and Lupyan 2018), using the open-source software Praat (Boersma and Weenink 2018). Another example comes from a set of studies that use a graphical signalling task to investigate the creation and evolution of novel communicative symbols.…”

The cognitive prerequisites for language: insights from iterated learning

“…Passing languages along chains of transmission provides a laboratory analogue for the transmission of real languages in the wild, and allows us to identify the conditions under which language-relevant features develop. These experimental techniques have been applied to study the emergence of symbols [21,22,23], combinatoriality [24,25,26], and compositionality [27,28,29]. Here, I focus on work on the evolution of compositional structure, which suggests that compositionality structure emerges when pressures from learning and use are both at play, but not when these pressures operate in isolation.…”

How culture and biology interact to shape language and the language faculty

“…These iterated learning and interactive techniques have been applied to study the emergence of symbols (Caldwell & Smith, 2012;Fay & Ellison, 2013;Garrod et al, 2007;Sulik, 2018), combinatoriality (Little, Eryilmaz, & de Boer, 2017;Roberts, Lewandowski, & Galantucci, 2015;Verhoef et al, 2014), and compositionality (Beckner, Pierrehumbert, & Hay, 2017;Kirby et al, 2008Kirby et al, , 2015. Following the emphasis in the Introduction on compositionality as a unique feature of human language, here I focus on work on the cultural evolution of compositional structure.…”