A model of prenatal acquisition of speech parameters

Bradley S. Seebach*, Nathan Intrator, Phil Lieberman, Leon N. Cooper

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

An unsupervised neural network model inductively acquires the ability to distinguish categorically the stop consonants of English, in a manner consistent with prenatal and early postnatal auditory experience, and without reference to any specialized knowledge of linguistic structure or the properties of speech. This argues against the common assumption that linguistic knowledge, and speech perception in particular, cannot be learned and must therefore be innately specified.

Original languageEnglish
Pages (from-to)7473-7476
Number of pages4
JournalProceedings of the National Academy of Sciences of the United States of America
Volume91
Issue number16
DOIs
StatePublished - 2 Aug 1994

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