Models of spoken‐word recognition

TLDR

Words are stored in a mental lexicon, and psycholinguistic models describe how lexical knowledge is stored and accessed during language use. The article summarizes key findings in spoken‑word recognition by humans. It describes how models of spoken‑word recognition account for these findings. Models agree that multiple word candidates are activated in parallel, that activation depends on signal‑lexicon match, and that candidates compete, but they disagree on information flow between processing levels and on the format of stored representations. Published in WIREs Cogn Sci 2012 (3:387–401), doi:10.1002/wcs.1178, under Linguistics > Computational Models of Language.

Abstract

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 This article is categorized under: Linguistics > Computational Models of Language