Recent research has shown that letter identity and letter position are not integral perceptual dimensions (e.g., jugde primes judge in word-recognition experiments). Most comprehensive computational models of visual word recognition (e.g., the interactive activation model, J. L. McClelland & D. E. Rumelhart, 1981, and its successors) assume that the position of each letter within a word is perfectly encoded. Thus, these models are unable to explain the presence of effects of letter transposition (trial-trail), letter migration (beard-bread), repeated letters (moose-mouse), or subset/superset effects (faulty-faculty). The authors extend R. Ratcliff's (1981) theory of order relations for encoding of letter positions and show that the model can successfully deal with these effects. The basic assumption is that letters in the visual stimulus have distributions over positions so that the representation of one letter will extend into adjacent letter positions. To test the model, the authors conducted a series of forced-choice perceptual identification experiments. The overlap model produced very good fits to the empirical data, and even a simplified 2-parameter model was capable of producing fits for 104 observed data points with a correlation coefficient of .91. Keywords lexical process; letter position coding; word recognition; modeling; perceptual matching A fundamental issue for any computational model of visual word recognition is how to represent the position in which letters are encoded. If letter position is not encoded, then anagrams like causal and casual or even desserts and stressed would not be able to be discriminated from each other. Some of the current computational models of visual word recognition make overly simplistic assumptions about how letter positions are coded, for example, that positions are perfectly encoded.The way in which letter positions are encoded needs to be a critical aspect of the front end of any computational model of visual word recognition. Letter position determines which words are considered orthographically similar and, therefore, which word representations are most likely to be selected for a particular string of letters. It also determines which words are likely to be confused with each other, especially when the stimulus is impoverished. Although the Correspondence to: Pablo Gomez.Correspondence concerning this article should be addressed to Pablo Gomez, DePaul University, Psychology Department, 2219 North Kenmore, Chicago, IL 60614. E-mail: pgomez1@condor.depaul.edu. Pablo Gomez, Psychology Department, DePaul University; Roger Ratcliff, Department of Psychology, The Ohio State University; Manuel Perea, Departmento de Metodología, Universitat de València, València, Spain. NIH Public Access Author ManuscriptPsychol Rev. Author manuscript; available in PMC 2008 December 9. Published in final edited form as:Psychol Rev. 2008 July ; 115(3): 577-600. doi:10.1037/a0012667. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript encoding of letter posit...

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Transposed-letter (TL) nonwords (e.g., jugde) can be easily misperceived as words, a fact that is somewhat inconsistent with the letter-position-coding schemes employed by most current models of visual word recognition. To examine this issue further, we conducted four masked semantic/associative priming experiments, using a lexical decision task. In Experiment 1, the related primes could be words, TL-internal nonwords, or replacement-letter (RL) nonwords (e.g., judge, jugde, or judpe, respectively; the target would be COURT). Relative to an unrelated condition, masked TL-internal primes produced a significant semantic/associative priming effect, an effect that was only slightly smaller than the priming effect for word primes. No effect, however, was observed for RL-nonword primes. In Experiment 2, the TL-nonword primes were created by switching the two final letters of the primes (e.g., judeg). The results again showed a semantic/associative priming effect for word primes, but not for TL-final nonword primes or for RL-nonword primes. Experiment 3 replicatedthe associative/semantic priming effect for TL-internal nonword primes, with, again, no effect for TL-final nonword primes. Finally, Experiment 4 again failed to yield a priming effect for TL-final nonword primes. The implications of these results for the choice of a letter-position-coding scheme in visual word recognition models are discussed.

This article describes a Windows program that enables users to obtain a broad range of statistics concerning the properties of word and nonword stimuli in Spanish, including word frequency, syllable frequency, bigram and biphone frequency, orthographic similarity, orthographic and phonological structure, concreteness, familiarity, imageability, valence, arousal, and age-of-acquisition measures. It is designed for use by researchers in psycholinguistics, particularly those concerned with recognition of isolated words. The program computes measures of orthographic similarity online, with respect to either a default vocabulary of 31,491 Spanish words or a vocabulary specified by the user. In addition to providing standard orthographic and phonological neighborhood measures, the program can be used to obtain information about other forms of orthographic similarity, such as transposed-letter similarity and embedded-word similarity. It is available, free of charge, from the following Web site: www.maccs.mq.edu.au/~colin/B-Pal.

This article introduces EsPal: a Web-accessible repository containing a comprehensive set of properties of Spanish words. EsPal is based on an extensible set of data sources, beginning with a 300 million token written database and a 460 million token subtitle database. Properties available include word frequency, orthographic structure and neighborhoods, phonological structure and neighborhoods, and subjective ratings such as imageability. Subword structure properties are also available in terms of bigrams and trigrams, biphones, and bisyllables. Lemma and part-of-speech information and their corresponding frequencies are also indexed. The website enables users either to upload a set of words to receive their properties or to receive a set of words matching constraints on the properties. The properties themselves are easily extensible and will be added over time as they become available. It is freely available from the following website: http:// www.bcbl.eu/databases/espal/. Keywords Word frequency . Subtitles . Word recognition . Corpus linguistics . PsycholinguisticsResearchers from a wide range of disciplines (e.g., neuroscience, artificial intelligence, psychology, linguistics, and education, among others) who work in the interdisciplinary area of language research (e.g., language acquisition, language processing, language learning, bilingualism, and computational linguistics) need quick and efficient access to information about specific properties of words. For example, word frequency is a dominant factor in accounting for visual word recognition speed as measured by lexical decision times (Forster & Chambers, 1973;Monsell, 1991) and eye fixation durations during reading (Rayner, 2009). Unsurprisingly, reading behavior as measured by, for example, lexical decision, naming, fixation times, and so on is affected by a wide range of other properties of words, including orthographic neighborhood