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Article published In: Diachronica
Vol. 38:2 (2021) ► pp.210–258

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Phylogenetic signal in phonotactics

ORCiD logo with link | The University of Queensland
ORCiD logo with link | Yale University
ORCiD logo with link | The University of Queensland | University of Surrey | Max Planck Institute for the Science of Human History
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Available under the Creative Commons Attribution (CC BY) 4.0 license.

For any use beyond this license, please contact the publisher at rights@benjamins.nl.

Published online: 2 February 2021
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https://doi.org/10.1075/dia.20004.mac
Abstract
Phylogenetic methods have broad potential in linguistics beyond tree inference. Here, we show how a phylogenetic approach opens the possibility of gaining historical insights from entirely new kinds of linguistic data – in this instance, statistical phonotactics. We extract phonotactic data from 112 Pama-Nyungan vocabularies and apply tests for phylogenetic signal, quantifying the degree to which the data reflect phylogenetic history. We test three datasets: (1) binary variables recording the presence or absence of biphones (two-segment sequences) in a lexicon (2) frequencies of transitions between segments, and (3) frequencies of transitions between natural sound classes. Australian languages have been characterized as having a high degree of phonotactic homogeneity. Nevertheless, we detect phylogenetic signal in all datasets. Phylogenetic signal is greater in finer-grained frequency data than in binary data, and greatest in natural-class-based data. These results demonstrate the viability of employing a new source of readily extractable data in historical and comparative linguistics.
Résumé
Les méthodes phylogénétiques ont le potentiel en linguistique pour faire de l’inférence des arbres. Ici, nous montrons comment une approche phylogénétique peut être utilisée avec de nouveaux types de données linguistiques – la phonotactique statistique. Nous quantifions le signal phylogénétique – le degré auquel les données reflètent la phylogénie – dans 112 vocabulaires de la familie Pama-Nyungan. Nous testons trois types de données : (1) des variables binaires enregistrant la présence ou l’absence de biphones (séquences de deux segments) (2) les fréquences de les transitions entre segments, et (3) les fréquences de transitions entre les classes sonores naturelles. Nous détectons un signal phylogénétique dans tous les ensembles de données. Le signal phylogénétique est plus élevé dans les données de fréquence plus détaillé que dans les données binaires, et le plus grand dans les données qui enregistrent des classes sonores. Ces résultats montrent que c’est possible d’employer une nouvelle source de données facilement extractibles en linguistique historique.
Zusammanfassung
Phylogenetische Methoden haben ein breites Potenzial in der Linguistik, das über die Inferenz von Bäumen hinausgeht. Hier zeigen wir, wie ein phylogenetischer Ansatz mit neuen Arten von Sprachdaten verwendet werden kann – in diesem Fall mit statistischer Phonotaktik. Wir quantifizieren das phylogenetische Signal – den Grad, in dem die Daten die Phylogenie widerspiegeln – in phonotaktischen Daten aus 112 Pama-Nyungan-Vokabularen. Wir testen drei Datensätze: (1) binäre Variablen, die das Vorhandensein oder Fehlen von Biphonen (Zwei-Segment-Sequenzen) aufzeichnen. (2) Häufigkeit von Übergängen zwischen Segmenten und (3) Häufigkeit von Übergängen zwischen natürlichen Lautklassen. Wir erkennen phylogenetische Signale in allen Datensätzen. Phylogenetische Signal ist in feinkörnigeren Frequenzdaten größer als in binären Daten und in Daten auf Basis natürlicher Klassen am größten. Diese Ergebnisse zeigen die Durchführbarkeit davon, eine neue Quelle leicht extrahierbarer Daten in der historischen und vergleichenden Linguistik einzusetzen.
Article outline
  • 1.Introduction
    • 1.1Motivations
    • 1.2Phonotactics as a source of historical signal
  • 2.Phylogenetic signal
  • 3.Materials
    • 3.1Language sample
    • 3.2Wordlists
    • 3.3Reference phylogeny
  • 4.Phylogenetic signal in binary phonotactic data
    • 4.1Results for binary phonotactic data
    • 4.2Robustness checks
  • 5.Phylogenetic signal in continuous phonotactic data
    • 5.1Robustness checks
    • 5.2Forward transitions versus backward transitions
    • 5.3Normalization of character values
  • 6.Phylogenetic signal in natural-class-based characters
    • 6.1Natural-class-based characters versus biphones
  • 7.Discussion
    • 7.1Overall robustness
    • 7.2Limitations
  • 8.Conclusion
  • Acknowledgements
  • Author contribution statement
  • Supplementary materials
  • Notes
  • References
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2023. Frequent violation of the sonority sequencing principle in hundreds of languages: how often and by which sequences?. Linguistic Typology 27:2 ► pp. 381 ff. DOI logo
Bowern, Claire
2022. Where have all the sound changes gone? Phonological stability and mechanisms of sound change. Linguistics Vanguard 8:s5 ► pp. 499 ff. DOI logo
Hübler, Nataliia & Simon J Greenhill
2022. Modelling admixture across language levels to evaluate deep history claims. Journal of Language Evolution 7:2 ► pp. 166 ff. DOI logo
Miceli, Luisa & Erich Round
2022. Where have all the sound changes gone? Examining the scarcity of evidence for regular sound change in Australian languages. Linguistics Vanguard 8:s5 ► pp. 509 ff. DOI logo
Phillips, Joshua & Claire Bowern
2022. Bayesian methods for ancestral state reconstruction in morphosyntax: Exploring the history of argument marking strategies in a large language family. Journal of Language Evolution 7:1 ► pp. 1 ff. DOI logo
Round, Erich, Rikker Dockum & Robin J. Ryder
2022. Evolution and Trade-Off Dynamics of Functional Load. Entropy 24:4 ► pp. 507 ff. DOI logo
Macklin-Cordes, Jayden L. & Erich R. Round
2020. Re-evaluating Phoneme Frequencies. Frontiers in Psychology 11 DOI logo
Macklin-Cordes, Jayden L. & Erich R. Round
2022. Challenges of sampling and how phylogenetic comparative methods help: with a case study of the Pama-Nyungan laminal contrast. Linguistic Typology 26:3 ► pp. 533 ff. DOI logo

This list is based on CrossRef data as of 8 december 2025. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.

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