Cracking arbitrariness
A data-driven study of auditory iconicity in spoken English
Bibliographic Data
| ID | 21641010 |
|---|---|
| Authors | Gregor Rehder (0000-0002-0597-9989, University of Milano-Bicocca, corresponding author), Massimo Marelli (0000-0001-5831-5441, University of Milano-Bicocca) |
| Year | 2025 |
| Volume | 32 |
| Issue | 3 |
| Pages | 1425-1442 |
| Publication date | 2025-06-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Psychonomic Bulletin & Review (JOURNAL) |
| Journal identifiers | ISSN: 1069-9384 • E-ISSN: 1531-5320 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.3758/s13423-024-02630-0 |
| PMID | 39779657 |
| OpenAlex | W4406159457 |
| Language | EN |
| Citations received | 1 |
| References cited | 83 |
Auditory iconic words display a phonological profile that imitates their referents’ sounds. Traditionally, those words are thought to constitute a minor portion of the auditory lexicon. In this article, we challenge this assumption by assessing the pervasiveness of onomatopoeia in the English auditory vocabulary through a novel data-driven procedure. We embed spoken words and natural sounds into a shared auditory space through (a) a short-time Fourier transform, (b) a convolutional neural network trained to classify sounds, and (c) a network trained on speech recognition. Then, we employ the obtained vector representations to measure their objective auditory resemblance. These similarity indexes show that imitation is not limited to some circumscribed semantic categories, but instead can be considered as a widespread mechanism underlying the structure of the English auditory vocabulary. We finally empirically validate our similarity indexes as measures of iconicity against human judgments
Arbitrariness · Iconicity · Imitation · Lexicon · Linguistics · Mental lexicon · Natural language processing · Speech recognition · Vocabulary · Categorization, perception, and language · Computer Science · Language, Metaphor, and Cognition · Multisensory perception and integration · Psychology · Artificial Intelligence
Bootstrap Methods and their Application
Arbitrariness, Iconicity, and Systematicity in Language
Iconicity in English and Spanish and Its Relation to Lexical Category and Age of Acquisition
Vector-Space Models of Semantic Representation From a Cognitive Perspective
Moving beyond Kučera and Francis
The bridge of iconicity
Sound symbolism facilitates early verb learning
Concreteness ratings for 40 thousand generally known English word lemmas
The Lancaster Sensorimotor Norms
Age-of-acquisition ratings for 30,000 English words
ImageNet classification with deep convolutional neural networks
A study in phonetic symbolism.
A solution to Plato's problem
Producing high-dimensional semantic spaces from lexical co-occurrence
Is “Huh?” a Universal Word? Conversational Infrastructure and the Convergent Evolution of Linguistic Items
Random effects structure for confirmatory hypothesis testing
Deep learning
The Origin of Speech
Playful iconicity
Two measures are better than one
Phonosemantic biases found in Leipzig-Jakarta lists of 66 languages
Revising an implicational hierarchy for the meanings of ideophones, with special reference to Japonic
Data-driven computational models reveal perceptual simulation in word processing
Iconicity ratings across the Japanese lexicon
Iconicity ratings really do measure iconicity, and they open a new window onto the nature of language
A phonological analysis of onomatopoeia in early word production
A Coefficient of Agreement for Nominal Scales
Wordform Similarity Increases With Semantic Similarity
Articulatory features of phonemes pattern to iconic meanings
Language is less arbitrary than one thinks
Onomatopoeia as a Figure and a Linguistic Principle
Advances in the Cross-Linguistic Study of Ideophones
What sound symbolism can and cannot do
Iconicity and Generative Grammar
| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 1 |