Quantifying Phonosemantic Iconicity Distributionally in 6 Languages

George Flint, Kaustubh Kislay


Abstract
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.
Anthology ID:
2025.ijcnlp-long.67
Volume:
Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics
Month:
December
Year:
2025
Address:
Mumbai, India
Editors:
Kentaro Inui, Sakriani Sakti, Haofen Wang, Derek F. Wong, Pushpak Bhattacharyya, Biplab Banerjee, Asif Ekbal, Tanmoy Chakraborty, Dhirendra Pratap Singh
Venues:
IJCNLP | AACL
SIG:
Publisher:
The Asian Federation of Natural Language Processing and The Association for Computational Linguistics
Note:
Pages:
1219–1237
Language:
URL:
https://preview.aclanthology.org/ingest-ijcnlp-aacl/2025.ijcnlp-long.67/
DOI:
Bibkey:
Cite (ACL):
George Flint and Kaustubh Kislay. 2025. Quantifying Phonosemantic Iconicity Distributionally in 6 Languages. In Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, pages 1219–1237, Mumbai, India. The Asian Federation of Natural Language Processing and The Association for Computational Linguistics.
Cite (Informal):
Quantifying Phonosemantic Iconicity Distributionally in 6 Languages (Flint & Kislay, IJCNLP-AACL 2025)
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PDF:
https://preview.aclanthology.org/ingest-ijcnlp-aacl/2025.ijcnlp-long.67.pdf