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Phonotactic Learning with Structure, Not Statistics

  • Stony Brook University
  • San Jose State University

Research output: Contribution to journalArticlepeer-review

Abstract

We provide empirical evidence against Wilson & Gallagher’s 2018 claim that statistics is necessary for phonotactic learning. We implement BUFIA, a feature-based nonstatistical learner and, using the same data and case study as Wilson & Gallagher, show that this non-statistical learner is equally successful at learning phonotactics as the Maximum Entropy-based learner they use. This counters their conclusion that non-statistical phonotactic learning is impossible, while supporting their advocacy for feature-based representations in phonotactic learning.

Original languageEnglish
JournalLinguistic Inquiry
DOIs
StateAccepted/In press - 2026

Keywords

  • abductive inference
  • computational phonology
  • phonotactic learning

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