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This paper presents a theory of visual word recognition that assumes that, in the tasks of word identification, lexical decision and semantic categorization, human readers behave as optimal Bayesian decision-makers. This leads to the development of a computational model of word recognition, the Bayesian Reader. The Bayesian Reader successfully simulates some of the most significant data on human reading. The model accounts for the nature of the function relating word-frequency to reaction time and identification threshold, the effects of neighborhood density and its interaction with frequency, and the variation in the pattern of neighborhood density effects seen in different experimental tasks. Both the general behavior of the model, and the way the model predicts different patterns of results in different tasks, follow entirely from the assumption that human readers approximate optimal Bayesian decision-makers.

Three eye movement experiments were conducted to examine the role of letter identity and letter position during reading. Before fixating on a target word within each sentence, readers were provided with a parafoveal preview that differed in the amount of useful letter identity and letter position information it provided. In Experiments 1 and 2, previews fell into 1 of 5 conditions: (a) identical to the target word, (b) a transposition of 2 internal letters, (c) a substitution of 2 internal letters, (d) a transposition of the 2 final letters, or (e) a substitution of the 2 final letters. In Experiment 3, the authors used a further set of conditions to explore the importance of external letter positions. The findings extend previous work and demonstrate that transposed-letter effects exist in silent reading. These experiments also indicate that letter identity information can be extracted from the parafovea outside of absolute letter position from the first 5 letters of the word to the right of fixation. Finally, the results support the notion that exterior letters play important roles in visual word recognition.

A masked priming lexical decision experiment was conducted to examine whether or not assignment of letter position in a word can be influenced by lexeme boundaries. The experiment was run in Basque, which is a strongly agglutinating language with a high proportion of inflected and compound words. Nonword primes were created by transposing two nonadjacent letters that crossed or did not cross morphological boundaries. Specifically, we compared morphologically complex prime–target pairs (e.g., arbigide–argibide) with orthographic controls (e.g., arkipide–argibide; note that argibide is a compound of argi 1 bide) and noncompound pairs (e.g., ortakila–orkatila) with orthographic controls (e.g., orbahila–orkatila). Results showed that transposed-letter effects were virtually the same for compound and noncompound words, both when the orthographic control condition was used as a baseline and when the identity condition was used as a baseline. Thus, transposed-letter similarity effects seem to be orthographic in nature. We examine the implications of these results for the models of visual word recognition. Two key issues in the literature on visual word recognition are (1) how internal letters are coded in the right positions within a word (i.e., how we distinguish between

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.

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Five theories of how letter position is coded are contrasted: position-specific slot-coding, Wickelcoding, open-bigram coding (discrete and continuous), and spatial coding. These theories make different predictions regarding the relative similarity of three different types of pairs of letter strings: substitution neighbors, neighbors-once-removed, and double-substitution neighbors. In Experiment 1, we used an illusory word paradigm and found that neighbor-once-removed similarity contexts resulted in fewer illusory word reports than substitution neighbors but more illusory words than double-substitution neighbors. In Experiments 2 and 3, we used a masked form priming technique with a lexical-decision task. The pattern of facilitation was as predicted by spatial coding but was incompatible with slot-coding, Wickelcoding, and both versions of open-bigram coding. These results provide further support for the SOLAR (self-organizing lexical aquisition and recognition) model of visual word identification.

Two key issues for models of visual-word recognition are the specification of an input coding scheme and whether these input coding schemes vary across orthographies. Here we report two masked priming lexical decision experiments that examine whether the ordering of the root letters plays a key role in producing transposed-letter effects in Arabic –a language characterized by concatenate morphology. In Experiment 1, letter transpositions involved two letters from the root, while in Experiment 2, letter transpositions involved one letter from the root and one letter from the word pattern. Results showed a reliable transposed-letter priming effect when the ordering of the letters of the root was kept intact (Experiment 2), but not when two root letters were transposed (Experiment 1). These findings support the view that the order of the root letters is only allowed a minimum degree of perceptual noise to avoid the negative impact of activating the ―wrong ‖ root family. Key words: transposed-letter, masked priming, morphology 2 Recent research has shown that a transposed-letter stimulus like jugde is very similar, perceptually to judge (e.g., faster recognition of jugde-JUDGE than jupte-JUDGE;

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We present two masked priming lexical decision experiments that examine whether a nonword prime activates associative/semantic information from their corresponding addition neighbor (e.g., lght-DARK via the addition neighbor light), producing associative/semantic priming. The rationale is the following: if a nonword prime with a missing letter produces a semantic/associative priming effect, this would clearly indicate that this nonword is activating the lexical/semantic representations of its base word, thereby reinforcing the models of visual-word recognition in which the orthographic representations produced by lght (or ligt) and light are quite similar (e.g., SOLAR, SERIOL, open-bigram, and overlap models). Results showed that the magnitude of the masked associative priming effect with subset primes is remarkably similar to the priming effect with the corresponding word prime. Furthermore, the magnitude of the associative priming effect was similar when the deleted letter was a vowel and when the deleted letter was a consonant. 2 In the past years, there has been growing interest in the search for an appropriate orthographic coding scheme for models of visual-word recognition. To achieve this goal, it is important to examine which words are being activated by a given stimulus item. There is