Sidestepping the Combinatorial Explosion: An Explanation of n-gram Frequency Effects Based on Naive Discriminative Learning.
Arnon and Snider ((2010). More than words: Frequency effects for multi-word phrases. Journal of Memory and Language, 62, 67–82) documented frequency effects for compositional four-grams independently of the frequencies of lower-order n-grams. They argue that comprehenders apparently store frequency...
| Publicado en: | Language & Speech Vol. 56; no. 3; pp. 329 - 348 |
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| Autores principales: | , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
Sep2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104223064&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104223064 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00238309 3YY jtl: Language & Speech issn: 00238309 maglogo: Y pubinfo: dt: Sep2013 vid: 56 iid: 3 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 104223064 90217183 90217183 10.1177/0023830913484896 104223064 ppf: 329 ppct: 19 formats: fmt: @attributes: type: P tig: atl: Sidestepping the Combinatorial Explosion: An Explanation of n-gram Frequency Effects Based on Naive Discriminative Learning. aug: au: Baayen, R Harald Hendrix, Peter Ramscar, Michael sug: subj: Learning Methods Theory Construction Classification Linguistics Language Processing Vocabulary Human Analytic Research Funding Source Speech Sample Repeated Measures Memory Cognition Psycholinguistics Semantics Concept Mapping Computer Simulation Probability Hypothesis ab: Arnon and Snider ((2010). More than words: Frequency effects for multi-word phrases. Journal of Memory and Language, 62, 67–82) documented frequency effects for compositional four-grams independently of the frequencies of lower-order n-grams. They argue that comprehenders apparently store frequency information about multi-word units. We show that n-gram frequency effects can emerge in a parameter-free computational model driven by naive discriminative learning, trained on a sample of 300,000 four-word phrases from the British National Corpus. The discriminative learning model is a full decomposition model, associating orthographic input features straightforwardly with meanings. The model does not make use of separate representations for derived or inflected words, nor for compounds, nor for phrases. Nevertheless, frequency effects are correctly predicted for all these linguistic units. Naive discriminative learning provides the simplest and most economical explanation for frequency effects in language processing, obviating the need to posit counters in the head for, and the existence of, hundreds of millions of n-gram representations. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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