The Weekly Newsletter of MIT Linguistics

MIT Linguistics Colloquium 4/30 - Bruce Hayes

Speaker: Bruce Hayes (UCLA)
Time: Friday, April 30, 2010, 3:30pm-5pm
Location: 32-141 (Stata Center)
Title: Accidentally-true constraints in phonotactic learning

The phonotactic learning system proposed by Hayes and Wilson (2008) follows the principle of the inductive baseline: it tries to learn phonotactics using as few principles of Universal Grammar (UG) as possible. The leading idea is that one could learn from such a system’s failures just as much as from its successes. For instance, the simplest version of the system fails to learn patterns of vowel harmony or unbounded stress, but it becomes able to learn them when amplified with UG principles corresponding to classical autosegmental tiers and metrical grids—thus forming a new kind of argument for such representations.

There is a second way in which failures of the baseline system might be informative: it could learn too much rather than too little. The baseline system involved a rather permissive concept of what can be a phonotactic constraint: a constraint’s structural description is simply a sequence of feature matrices, each representing one of the natural classes of segments in a language. Where there are C natural classes and constraints are allowed to have n matrices, there will be Cn possible constraints. In actual practice, this can be a very large number.

With such a large hypothesis space, it is imaginable that the system might find constraints that are “accidentally true”: they have few or no exceptions in the lexicon, but are not apprehended by native speakers and play no role in their phonotactic intuitions. Hayes and Wilson’s learning simulation for the phonotactics of Wargamay may have done this. While the 100 constraints the system learned included 43 that successfully recapitulate the known phonotactic restrictions of this language (Dixon 1981), a further 57 constraints were discovered that struck the authors as complex and phonologically mystifying. An example is *[–approx, +cor][+high,+back,–main][–cons], which forbids sequences of coronal noncontinuants ([d, ?, n, ?]), followed by unstressed or secondary-stressed [u, u?], followed by a vowel or glide. Almost any phonologist would agree that this an unlikely configuration for a language to forbid.

Do real speakers apprehend constraints of this kind? I will report an experimental study now in progress that addresses this question for English. When trained on English data, the Hayes/Wilson system behaves just as it did with Wargamay, learning both sensible and accidental-seeming constraints. The experiment used 20 nonce-word quadruplets, each containing:

  1. a word that violates exactly one constraint, of the “accidental” type
  2. a word that is violation-free but otherwise similar to (1)
  3. a word that violates exactly one constraint that would be considered by phonologists to be natural (e.g. a sonority-sequencing constraint), and has a weight similar to the constraint in (1)
  4. a violation-free control word similar to (3).

The results of the experiment indicate that the (1)-(2) difference is considerably smaller than the (3)-(4) difference—i.e. that unnatural constraints really do have a weaker effect on native speaker judgment than natural constraints.

I will then explore two hypotheses that might explain the disparity: (a) a statistical approach based on comparing the explanatory power of added constraints (Wilson 2009); (b) a UG-based approach under which language learners are biased (Wilson 2006) to assign the natural constraints high weights relative to unnatural ones.


  • Dixon, Robert M. W. 1981. Wargamay. In Handbook of Australian languages, volume II, ed. Robert M. W. Dixon and Barry J. Blake, 1–144. Amsterdam: John Benjamins.
  • Hayes, Bruce and Colin Wilson (2008) A maximum entropy model of phonotactics and phonotactic learning. Linguistic Inquiry 39: 379-440.
  • Wilson, Colin and Marieke Obdeyn (2009) Simplifying subsidiary theory: statistical evidence from Arabic, Muna, Shona, and Wargamay. Ms., Johns Hopkins University.