dc.contributor.author | Hayes, J. | |
dc.contributor.author | Murphy, V. | |
dc.contributor.author | Davey, N. | |
dc.contributor.author | Smith, Pamela | |
dc.date.accessioned | 2012-05-28T10:01:49Z | |
dc.date.available | 2012-05-28T10:01:49Z | |
dc.date.issued | 2003 | |
dc.identifier.citation | Hayes , J , Murphy , V , Davey , N & Smith , P 2003 , How the constraints on English compound production might be learnt from the linguistic input : evidence from 4 connectionist models . in Proceedings of NCPW 2003 . | |
dc.identifier.other | dspace: 2299/796 | |
dc.identifier.uri | http://hdl.handle.net/2299/8613 | |
dc.description.abstract | Native English speakers include irregular plurals in English noun-noun compounds (e.g. mice chaser) more frequently than regular plurals (e.g. *rats chaser) (Gordon, 1985). This dissociation in inflectional morphology has been argued to stem from an internal and innate morphological constraint as it is thought that the input to which English speaking children are exposed is insufficient to signal that regular plurals are prohibited in compounds but irregulars might be allowed (Marcus, Brinkmann, Clahsen, Wiese & Pinker, 1995). In addition, this dissociation in English compounds has been invoked to support the idea that regular and irregular morphology are mediated by separate cognitive systems (Pinker, 1999). The evidence of the neural network models presented here is used to support an alternative view that the constraint on English compounds can be derived from the general frequencies and patterns in which the two types of plural (regular and irregular) in conjunction with the possessive morpheme occur in the input | en |
dc.format.extent | 121992 | |
dc.language.iso | eng | |
dc.relation.ispartof | Proceedings of NCPW 2003 | |
dc.title | How the constraints on English compound production might be learnt from the linguistic input : evidence from 4 connectionist models | en |
dc.contributor.institution | School of Computer Science | |
dc.contributor.institution | Science & Technology Research Institute | |
dc.contributor.institution | School of Engineering and Technology | |
rioxxterms.type | Other | |
herts.preservation.rarelyaccessed | true | |