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      The British Lexicon Project: Lexical decision data for 28,730 monosyllabic and disyllabic English words

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          Abstract

          We present a new database of lexical decision times for English words and nonwords, for which two groups of British participants each responded to 14,365 monosyllabic and disyllabic words and the same number of nonwords for a total duration of 16 h (divided over multiple sessions). This database, called the British Lexicon Project (BLP), fills an important gap between the Dutch Lexicon Project (DLP; Keuleers, Diependaele, & Brysbaert, Frontiers in Language Sciences. Psychology, 1, 174, 2010) and the English Lexicon Project (ELP; Balota et al., 2007), because it applies the repeated measures design of the DLP to the English language. The high correlation between the BLP and ELP data indicates that a high percentage of variance in lexical decision data sets is systematic variance, rather than noise, and that the results of megastudies are rather robust with respect to the selection and presentation of the stimuli. Because of its design, the BLP makes the same analyses possible as the DLP, offering researchers with a new interesting data set of word-processing times for mixed effects analyses and mathematical modeling. The BLP data are available at http://crr.ugent.be/blp and as Electronic Supplementary Materials.

          Electronic supplementary material

          The online version of this article (doi:10.3758/s13428-011-0118-4) contains supplementary material, which is available to authorized users.

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          Most cited references31

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          DRC: a dual route cascaded model of visual word recognition and reading aloud.

          This article describes the Dual Route Cascaded (DRC) model, a computational model of visual word recognition and reading aloud. The DRC is a computational realization of the dual-route theory of reading, and is the only computational model of reading that can perform the 2 tasks most commonly used to study reading: lexical decision and reading aloud. For both tasks, the authors show that a wide variety of variables that influence human latencies influence the DRC model's latencies in exactly the same way. The DRC model simulates a number of such effects that other computational models of reading do not, but there appear to be no effects that any other current computational model of reading can simulate but that the DRC model cannot. The authors conclude that the DRC model is the most successful of the existing computational models of reading.
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            Orthographic processing in visual word recognition: a multiple read-out model.

            A model of orthographic processing is described that postulates read-out from different information dimensions, determined by variable response criteria set on these dimensions. Performance in a perceptual identification task is simulated as the percentage of trials on which a noisy criterion set on the dimension of single word detector activity is reached. Two additional criteria set on the dimensions of total lexical activity and time from stimulus onset are hypothesized to be operational in the lexical decision task. These additional criteria flexibly adjust to changes in stimulus material and task demands, thus accounting for strategic influences on performance in this task. The model unifies results obtained in response-limited and data-limited paradigms and helps resolve a number of inconsistencies in the experimental literature that cannot be accommodated by other current models of visual word recognition.
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              Wuggy: a multilingual pseudoword generator.

              Pseudowords play an important role in psycholinguistic experiments, either because they are required for performing tasks, such as lexical decision, or because they are the main focus of interest, such as in nonword-reading and nonce-inflection studies. We present a pseudoword generator that improves on current methods. It allows for the generation of written polysyllabic pseudowords that obey a given language's phonotactic constraints. Given a word or nonword template, the algorithm can quickly generate pseudowords that match the template in subsyllabic structure and transition frequencies without having to search through a list with all possible candidates. Currently, the program is available for Dutch, English, German, French, Spanish, Serbian, and Basque, and, with little effort, it can be expanded to other languages.
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                Author and article information

                Contributors
                +32-9-2649432 , +32-9-2646496 , emmanuel.keuleers@ugent.be
                Journal
                Behav Res Methods
                Behav Res Methods
                Behavior Research Methods
                Springer-Verlag (New York )
                1554-351X
                1554-3528
                1 July 2011
                1 July 2011
                March 2012
                : 44
                : 1
                : 287-304
                Affiliations
                [1 ]Department of Experimental Psychology, Ghent University, Henri Dunantlaan 2, B-9000 Gent, Belgium
                [2 ]Department of Psychology, Royal Holloway, University of London, London, UK
                Article
                118
                10.3758/s13428-011-0118-4
                3278621
                21720920
                1289a231-b846-4386-b1b9-6a1c25f0de3b
                © The Author(s) 2011
                History
                Categories
                Article
                Custom metadata
                © Psychonomic Society, Inc. 2012

                Clinical Psychology & Psychiatry
                visual word recognition,trial level analysis,virtual experiments,british english,megastudy,reaction times,lexical decision

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