Rules vs. Analogy in English Past Tenses:
A Computational/Experimental Study

Cognition 90 (2003) 119–161
Adam Albright
Department of Linguistics, MIT
      Bruce Hayes
Department of Linguistics, UCLA


Are morphological patterns learned in the form of rules? Some models deny this, attributing all morphology to analogical mechanisms. The dual mechanism model (Pinker & Prince, 1988) posits that speakers do internalize rules, but that these rules are few and cover only regular processes; the remaining patterns are attributed to analogy. This article advocates a third approach, which uses multiple stochastic rules and no analogy. Our model employs inductive learning to discover multiple rules, and assigns them confidence scores based on their performance in the lexicon.

Our model is supported over the two alternatives by new "wug test" data on English past tenses. As our model predicts, participant ratings of novel pasts depend on the phonological shape of the stem, both for irregulars and, surprisingly, also for regulars. The latter observation cannot be explained under the dual mechanism approach, which derives all regulars with a single rule. To evaluate the alternative hypothesis that all morphology is analogical, we implemented a purely analogical model, which evaluates novel pasts based solely on their similarity to existing verbs. Tested against experimental data, this analogical model also failed in key respects: it could not locate patterns that require abstract structural characterizations, and it favored implausible responses based on single, highly similar exemplars. We conclude that speakers extend morphological patterns based on abstract structural properties, of a kind appropriately described with rules.




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Last updated:  January 24, 2017