Papers on Hungarian Vowel Harmony

The Hungarian vowel harmony system is fascinating for its blend of disparate influences.  On top of a relatively straightforward system of backness assimilation is overlaid a great number of additional complexities, involving free variation, idiosyncratic behavior of particular lexical items, and peripheral phonological constraints of the kind that Bach and Harms (1972) called "crazy".  The system is an ideal arena for applying and honing tools of phonological theory whose use is currently spreading throughout the field:  corpus study, experimentation, quantitative constraint-based models, and algorithms for learning.  These methods are used in both of the papers below.

I've enjoyed doing this work as part of an excellent research team whose members share expertise in experimentation, modeling, theory, and the phonology of Hungarian.

Map of Hungary showing location of experimental participans

Map of Hungary showing where our experimental participants came from.  The large dot is Budapest.

Stochastic Phonological Knowledge:  The Case of Hungarian Vowel Harmony

by Bruce Hayes and Zsuzsa Cziráky Londe

Preprint version. Published in Phonology 23:59-104 (2006).


In Hungarian, stems ending in a back vowel plus one or more neutral vowels show unusual behavior: for such stems, the otherwise-general process of vowel harmony is lexically idiosyncratic. Particular stems can take front suffixes, take back suffixes, or vacillate. Yet at a statistical level, the patterning among these stems is lawful: in the aggregate, they obey principles that relate the propensity to take back or front harmony to the height of the rightmost vowel and to the number of neutral vowels.

We argue that this patterned statistical variation in the Hungarian lexicon is internalized by native speakers. Our evidence is that they replicate the pattern when they are asked to apply harmony to novel stems in a "wug" test (Berko 1958). Our test results match quantitative data about the Hungarian lexicon, gathered with an automated Web search. We model the speakers' knowledge and intuitions with a grammar based on the dual listing/generation model of Zuraw (2000), then show how the constraint rankings of this grammar can be learned by algorithm.

Supporting files

Natural and Unnatural Constraints in Hungarian Vowel Harmony,

by Bruce Hayes, Kie Zuraw, Péter Siptár, and Zsuzsa Londe

Language 85: 822-863 (2009)


Phonological constraints can, in principle, be classified according to whether they are natural (founded in principles of Universal Grammar (UG)) or unnatural (arbitrary, learned inductively from the language data). Recent work has used this distinction as the basis for arguments about the role of UG in learning. Some languages have phonological patterns that arguably reflect unnatural constraints. With experimental testing, one can assess whether such patterns are actually learned by native speakers. Becker, Ketrez, and Nevins (2007), testing speakers of Turkish, suggest that they do indeed go unlearned. They interpret this result with a strong UG position: humans are unable to learn data patterns not backed by UG principles.

This article pursues the same research line, locating similarly unnatural data patterns in the vowel harmony system of Hungarian, such as the tendency (among certain stem types) for a final bilabial stop to favor front harmony. Our own test leads to the opposite conclusion to Becker et al.: Hungarians evidently do learn the unnatural patterns.

To conclude we consider a bias account-that speakers are able to learn unnatural environments, but devalue them relative to natural ones. We outline a method for testing the strength of constraints as learned by speakers against the strength of the corresponding patterns in the lexicon, and show that it offers tentative support for the hypothesis that unnatural constraints are disfavored by language learners.

Download the paper (pdf format)

Typo:  p. 830, maradék(nat) should be maradék(nak) 'remainder-dat' (already fixed in the downloadable version given here).

Supporting files