# Re-evaluating phoneme frequencies

arXiv: https://arxiv.org/abs/2006.05206 · HTML: https://mlsanity.com/paper/2006.05206/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Jun 2020.

## Built on by (most cited first, 5 of 5)

- [Efficiently Identifying Low-Quality Language Subsets in Multilingual Datasets: A Case Study on a Large-Scale Multilingual Audio Dataset](https://mlsanity.com/paper/2410.04292/) (2024)
- [The Distribution of Phoneme Frequencies across the World's Languages: Macroscopic and Microscopic Information-Theoretic Models](https://mlsanity.com/paper/2603.02860/) (2026)
- [Evolution and trade-off dynamics of functional load](https://mlsanity.com/paper/2112.12224/) (2021)
- [Challenges of sampling and how phylogenetic comparative methods help: With a case study of the Pama-Nyungan laminal contrast](https://mlsanity.com/paper/2201.00195/) (2022)
- [Modelling the Diachronic Emergence of Phoneme Frequency Distributions](https://mlsanity.com/paper/2603.09503/) (2026)

## Abstract (arXiv)

Causal processes can give rise to distinctive distributions in the linguistic variables that they affect. Consequently, a secure understanding of a variable's distribution can hold a key to understanding the forces that have causally shaped it. A storied distribution in linguistics has been Zipf's law, a kind of power law. In the wake of a major debate in the sciences around power-law hypotheses and the unreliability of earlier methods of evaluating them, here we re-evaluate the distributions claimed to characterize phoneme frequencies. We infer the fit of power laws and three alternative distributions to 166 Australian languages, using a maximum likelihood framework. We find evidence supporting earlier results, but also nuancing them and increasing our understanding of them. Most notably, phonemic inventories appear to have a Zipfian-like frequency structure among their most-frequent members (though perhaps also a lognormal structure) but a geometric (or exponential) structure among the least-frequent. We compare these new insights the kinds of causal processes that affect the evolution of phonemic inventories over time, and identify a potential account for why, despite there being an important role for phonetic substance in phonemic change, we could still expect inventories with highly diverse phonetic content to share similar distributions of phoneme frequencies. We conclude with priorities for future work in this promising program of research.