English

Kiki or Bouba? Sound Symbolism in Vision-and-Language Models

Computer Vision and Pattern Recognition 2024-04-03 v3 Computation and Language Machine Learning

Abstract

Although the mapping between sound and meaning in human language is assumed to be largely arbitrary, research in cognitive science has shown that there are non-trivial correlations between particular sounds and meanings across languages and demographic groups, a phenomenon known as sound symbolism. Among the many dimensions of meaning, sound symbolism is particularly salient and well-demonstrated with regards to cross-modal associations between language and the visual domain. In this work, we address the question of whether sound symbolism is reflected in vision-and-language models such as CLIP and Stable Diffusion. Using zero-shot knowledge probing to investigate the inherent knowledge of these models, we find strong evidence that they do show this pattern, paralleling the well-known kiki-bouba effect in psycholinguistics. Our work provides a novel method for demonstrating sound symbolism and understanding its nature using computational tools. Our code will be made publicly available.

Keywords

Cite

@article{arxiv.2310.16781,
  title  = {Kiki or Bouba? Sound Symbolism in Vision-and-Language Models},
  author = {Morris Alper and Hadar Averbuch-Elor},
  journal= {arXiv preprint arXiv:2310.16781},
  year   = {2024}
}

Comments

Accepted to NeurIPS 2023 (spotlight). Project webpage: https://kiki-bouba.github.io/