Rules vs. analogy in English past tenses: A computational/experimental study. Albright, A. & Hayes, B. Cognition, 90(2):119-61, 2003.
abstract   bibtex   
Are morphological patterns learned in the form of rules? Some models deny this, attributing all morphology to analogical mechanisms. The dual mechanism model (Pinker, S., & Prince, A. (1998). On language and connectionism: analysis of a parallel distributed processing model of language acquisition. Cognition, 28, 73-193) 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. We propose a model that 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, which show that 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.
@Article{Albright2003,
  author   = {Albright, Adam and Hayes, Bruce},
  journal  = {Cognition},
  title    = {Rules vs. analogy in {E}nglish past tenses: {A} computational/experimental study.},
  year     = {2003},
  number   = {2},
  pages    = {119-61},
  volume   = {90},
  abstract = {Are morphological patterns learned in the form of rules? Some models
	deny this, attributing all morphology to analogical mechanisms. The
	dual mechanism model (Pinker, S., & Prince, A. (1998). On language
	and connectionism: analysis of a parallel distributed processing
	model of language acquisition. Cognition, 28, 73-193) 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. We propose a model that 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, which show that 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.},
  keywords = {Computing Methodologies, Human, Language, Learning, Mental Processes, Models, Theoretical, Stochastic Processes, Support, U.S. Gov't, Non-P.H.S., 14599751},
}

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