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Quantifying Phonosemantic Iconicity Distributionally in 6 Languages

arXiv 2510.14040 ↗First posted 15 Oct 2025cs.CLcited by 0

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Abstract (arXiv)

Language is, as commonly theorized, largely arbitrary. Yet, systematic relationships between phonetics and semantics have been observed in many specific cases. To what degree could those systematic relationships manifest themselves in large scale, quantitative investigations--both in previously identified and unidentified phenomena? This work undertakes a distributional approach to quantifying phonosemantic iconicity at scale across 6 diverse languages (English, Spanish, Hindi, Finnish, Turkish, and Tamil). In each language, we analyze the alignment of morphemes' phonetic and semantic similarity spaces with a suite of statistical measures, and discover an array of interpretable phonosemantic alignments not previously identified in the literature, along with crosslinguistic patterns. We also analyze 5 previously hypothesized phonosemantic alignments, finding support for some such alignments and mixed results for others.

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References · 6

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2016Enriching Word Vectors with Subword Informationcited by 1,578
  3. 2020Stanza: A Python Natural Language Processing Toolkit for Many Human Languagescited by 719
  4. 2024The Impact of Visual Information in Chinese Characters: Evaluating Large Models' Ability to Recognize and Utilize Radicalscited by 10
  5. 2019VCWE: Visual Character-Enhanced Word Embeddingscited by 4
  6. 2024Labeled Morphological Segmentation with Semi-Markov Modelscited by 2

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