# A Deep Generative Model of Vowel Formant Typology

arXiv: https://arxiv.org/abs/1807.02745 · HTML: https://mlsanity.com/paper/1807.02745/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Jul 2018.

## Built on by (most cited first, 3 of 3)

- [On the Generalisation Capabilities of Fisher Vector based Face Presentation Attack Detection](https://mlsanity.com/paper/2103.01721/) (2021)
- [Colexifications for Bootstrapping Cross-lingual Datasets: The Case of Phonology, Concreteness, and Affectiveness](https://mlsanity.com/paper/2306.02646/) (2023)
- [Tonguescape: Exploring Language Models Understanding of Vowel Articulation](https://mlsanity.com/paper/2501.17643/) (2025)

## Abstract (arXiv)

What makes some types of languages more probable than others? For instance, we know that almost all spoken languages contain the vowel phoneme /i/; why should that be? The field of linguistic typology seeks to answer these questions and, thereby, divine the mechanisms that underlie human language. In our work, we tackle the problem of vowel system typology, i.e., we propose a generative probability model of which vowels a language contains. In contrast to previous work, we work directly with the acoustic information -- the first two formant values -- rather than modeling discrete sets of phonemic symbols (IPA). We develop a novel generative probability model and report results based on a corpus of 233 languages.