Literature DB >> 26301470

Models of spoken-word recognition.

Andrea Weber1, Odette Scharenborg1.   

Abstract

All words of the languages we know are stored in the mental lexicon. Psycholinguistic models describe in which format lexical knowledge is stored and how it is accessed when needed for language use. The present article summarizes key findings in spoken-word recognition by humans and describes how models of spoken-word recognition account for them. Although current models of spoken-word recognition differ considerably in the details of implementation, there is general consensus among them on at least three aspects: multiple word candidates are activated in parallel as a word is being heard, activation of word candidates varies with the degree of match between the speech signal and stored lexical representations, and activated candidate words compete for recognition. No consensus has been reached on other aspects such as the flow of information between different processing levels, and the format of stored prelexical and lexical representations. WIREs Cogn Sci 2012, 3:387-401. doi: 10.1002/wcs.1178 For further resources related to this article, please visit the WIREs website.
Copyright © 2012 John Wiley & Sons, Ltd.

Entities:  

Year:  2012        PMID: 26301470     DOI: 10.1002/wcs.1178

Source DB:  PubMed          Journal:  Wiley Interdiscip Rev Cogn Sci        ISSN: 1939-5078


  17 in total

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Journal:  Hear Res       Date:  2018-05-04       Impact factor: 3.208

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7.  Listeners can anticipate future segments before they identify the current one.

Authors:  Kayleen E Schreiber; Bob McMurray
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8.  Grammatical context constrains lexical competition in spoken word recognition.

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Journal:  Mem Cognit       Date:  2014-05

9.  The Presence of Background Noise Extends the Competitor Space in Native and Non-Native Spoken-Word Recognition: Insights from Computational Modeling.

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Journal:  Cogn Sci       Date:  2022-02

10.  Lexical Access Changes Based on Listener Needs: Real-Time Word Recognition in Continuous Speech in Cochlear Implant Users.

Authors:  Francis X Smith; Bob McMurray
Journal:  Ear Hear       Date:  2022-01-21       Impact factor: 3.562

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