title: A model of prenatal acquisition of speech parameters.
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.
authors.affiliation: Department of Neuroscience, Brown University, Providence, RI 02912.
authors.forename: B S
authors.initials: BS
authors.lastname: Seebach
authors.forename: N
authors.initials: N
authors.lastname: Intrator
authors.forename: P
authors.initials: P
authors.lastname: Lieberman
authors.forename: L N
authors.initials: LN
authors.lastname: Cooper
mesh_terms: D005333:Fetus; D006309:Hearing; D006801:Humans; D007858:Learning; D008959:Models, Neurological; D016571:Neural Networks, Computer; D009446:Neurobiology / Q000379:methods; D013060:Speech