A spatial model of the phonological and semantic representations involved in printed word recognition

2001 ◽  
Author(s):  
Aicha Rouibah ◽  
Sabine Ploux
Keyword(s):  
Word Recognition ◽  
Spatial Model ◽  
Semantic Representations ◽  
Printed Word

Effects of Illustrations on Reading Performance: Implications for Further LD Research

1980 ◽  
Vol 3 (2) ◽  
pp. 60-70 ◽  
Author(s):  
Jean R. Harber
Keyword(s):  
Reading Comprehension ◽  
Word Recognition ◽  
Learning Disabled ◽  
Reading Performance ◽  
Beginning Readers ◽  
Disabled Children ◽  
The Poor ◽  
Research Findings ◽  
Printed Word ◽  
Low Ability

This article reviews available research findings on the influence of illustrations on the reading performance (i.e., word recognition and reading comprehension) of beginning readers in general and in specific subgroups of beginning readers (e.g., poor achievers, low-ability students). Findings suggest that the presence of illustrations interferes with poorly achieving and low-ability children's performance on word recognition tasks and that illustrations are of questionable value to such children's performance on reading comprehension tasks. The possibility that illustrations serve to distract the poor reader's attention from the printed word is discussed. The inability to filter out extraneous stimuli and focus selectively on a task frequently seen in learning disabled children is presented in terms of selective attention theory. Suggestions are offered for further research on the effect of illustrations on learning disabled youngsters' reading performance.

scholarly journals Semantic diversity is best measured with unscaled vectors: Reply to Cevoli, Watkins and Rastle (2020)

2021 ◽  
Author(s):  
Paul Hoffman ◽  
Matthew A. Lambon Ralph ◽  
Timothy T. Rogers
Keyword(s):  
Word Recognition ◽  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Word Meaning ◽  
Singular Values ◽  
Semantic Representations ◽  
Diversity Measure ◽  
Contextual Variability ◽  
Original Measure ◽  
Special Case

AbstractSemantic diversity refers to the degree of semantic variability in the contexts in which a particular word is used. We have previously proposed a method for measuring semantic diversity based on latent semantic analysis (LSA). In a recent paper, Cevoli et al. (2020) attempted to replicate our method and obtained different semantic diversity values. They suggested that this discrepancy occurred because they scaled their LSA vectors by their singular values, while we did not. Using their new results, they argued that semantic diversity is not related to ambiguity in word meaning, as we originally proposed. In this reply, we demonstrate that the use of unscaled vectors provides better fits to human semantic judgements than scaled ones. Thus we argue that our original semantic diversity measure should be preferred over the Cevoli et al. version. We replicate Cevoli et al.’s analysis using the original semantic diversity measure and find (a) our original measure is a better predictor of word recognition latencies than the Cevoli et al. equivalent and (b) that, unlike Cevoli et al.’s measure, our semantic diversity is reliably associated with a measure of polysemy based on dictionary definitions. We conclude that the Hoffman et al. semantic diversity measure is better-suited to capturing the contextual variability among words and that words appearing in a more diverse set of contexts have more variable semantic representations. However, we found that homonyms did not have higher semantic diversity values than non-homonyms, suggesting that the measure does not capture this special case of ambiguity.

scholarly journals Predictive pre-activation of orthographic and lexical-semantic representations facilitates visual word recognition

2020 ◽  
Author(s):  
Susanne Eisenhauer ◽  
Benjamin Gagl ◽  
Christian J. Fiebach
Keyword(s):  
Word Recognition ◽  
Visual Word Recognition ◽  
Predictive Coding ◽  
Visual Word ◽  
Semantic Representations ◽  
Lexical Semantic ◽  
Brain Responses ◽  
Linguistic Representations ◽  
Context Dependent ◽  
Stimulus Features

AbstractTo a crucial extent, the efficiency of reading results from the fact that visual word recognition is faster in predictive contexts. Predictive coding models suggest that this facilitation results from pre-activation of predictable stimulus features across multiple representational levels before stimulus onset. Still, it is not sufficiently understood which aspects of the rich set of linguistic representations that are activated during reading – visual, orthographic, phonological, and/or lexical-semantic – contribute to context-dependent facilitation. To investigate in detail which linguistic representations are pre-activated in a predictive context and how they affect subsequent stimulus processing, we combined a well-controlled repetition priming paradigm, including words and pseudowords (i.e., pronounceable nonwords), with behavioral and magnetoencephalography measurements. For statistical analysis, we used linear mixed modeling, which we found had a higher statistical power compared to conventional multivariate pattern decoding analysis. Behavioral data from 49 participants indicate that word predictability (i.e., context present vs. absent) facilitated orthographic and lexical-semantic, but not visual or phonological processes. Magnetoencephalography data from 38 participants show sustained activation of orthographic and lexical-semantic representations in the interval before processing the predicted stimulus, suggesting selective pre-activation at multiple levels of linguistic representation as proposed by predictive coding. However, we found more robust lexical-semantic representations when processing predictable in contrast to unpredictable letter strings, and pre-activation effects mainly resembled brain responses elicited when processing the expected letter string. This finding suggests that pre-activation did not result in ‘explaining away’ predictable stimulus features, but rather in a ‘sharpening’ of brain responses involved in word processing.Impact StatementVisual word recognition is facilitated in predictive contexts. Predictive coding postulates that context-dependent facilitation involves the pre-activation of expected stimulus features, but it is not clear on which linguistic representations this mechanism relies during word recognition. Combining magnetoencephalography with high-powered linear mixed modeling, we show that context-dependent facilitation relies on pre-activation of orthographic and lexical-semantic representations in neuronal signals before actually perceiving an expected word.

scholarly journals Arabic Printed Word Recognition Using Windowed Bernoulli HMMs

2013 ◽  
pp. 330-339
Author(s):  
Ihab Khoury ◽  
Adrià Giménez ◽  
Alfons Juan ◽  
Jesús Andrés-Ferrer
Keyword(s):  
Word Recognition ◽  
Printed Word

Time Course of the Second Morpheme Processing During Spoken Disyllabic Compound Word Recognition in Chinese

2018 ◽  
Vol 61 (11) ◽  
pp. 2796-2803
Author(s):  
Wei Shen ◽  
Zhao Li ◽  
Xiuhong Tong
Keyword(s):  
Word Recognition ◽  
Target Word ◽  
Time Course ◽  
Mixed Model ◽  
Time Window ◽  
Spoken Word Recognition ◽  
Visual Display ◽  
Spoken Word ◽  
Printed Word ◽  
Whole Word

Purpose This study aimed to investigate the time course of meaning activation of the 2nd morpheme processing of compound words during Chinese spoken word recognition using eye tracking technique with the printed-word paradigm. Method In the printed-word paradigm, participants were instructed to listen to a spoken target word (e.g., “大方”, /da4fang1/, generous) while presented with a visual display composed of 3 words: a morphemic competitor (e.g., “圆形”, /yuan2xing2/, circle), which was semantically related to the 2nd morpheme (e.g., “方”, /fang1/, square) of the spoken target word; a whole-word competitor (e.g., “吝啬”, /lin4se4/, stingy), which was semantically related to the spoken target word at the whole-word level; and a distractor, which was semantically related to neither the morpheme or the whole target word. Participants were asked to respond whether the spoken target word was on the visual display or not, and their eye movements were recorded. Results The logit mixed-model analysis showed both the morphemic competitor and the whole-word competitor effects. Both the morphemic and whole-word competitors attracted more fixations than the distractor. More importantly, the 2nd-morphemic competitor effect occurred at a relatively later time window (i.e., 1000–1500 ms) compared with the whole-word competitor effect (i.e., 200–1000 ms). Conclusion Findings in this study suggest that semantic information of both the 2nd morpheme and the whole word of a compound was activated in spoken word recognition and that the meaning activation of the 2nd morpheme followed the activation of the whole word.

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