Image-Based Word Frequency Norms

Traditional word frequency norms are derived from text corpora. This article discusses word frequency derived from domain-specific visual corpora, where words are used to denote or label content in real-world scene images from large-scale datasets. These image-based frequency estimates capture aspects of language usage missing from traditional frequency measures, reflecting their nature at the intersection between language and vision. The article reviews the main approaches for creating these metrics (as well as measures derived from them), discusses studies validating their role as hybrid measures, and highlights their utility in complementing traditional word frequency norms to better address theoretical questions empirically.