Word recognition performance varies systematically as a function of where the eyes fixate in the word. Performance is maximal with the eye slightly left of the center of the word, and decreases drastically to both sides of this 'Optimal Viewing Position'. While manipulations of lexical factors have only marginal effects on this phenomenon, previous studies have pointed to a relation between the viewing position effect and letter legibility: When letter legibility drops, the viewing position effect becomes (...) more exaggerated. To further investigate this phenomenon, we improved letter legibility by magnifying letter size in a way that was proportional to the.. (shrink)

Frost's article advocates for universal models of reading and critiques recent models that concentrate in what has been described as “cracking the orthographic code.” Although the challenge to develop models that can account for word recognition beyond Indo-European languages is welcomed, we argue that reading models should also be constrained by general principles of visual processing and object recognition.

The neural substrates of context effects in word perception are still largely unclear. Interhemispheric priming phenomena in word recognition, typically observed in normal subjects, are absent in commissurotomized patients. This suggests that callosal fibers may provide contextual integration. In addition, certain characteristics of human frontal cortical fields subserving sensorimotor learning, as investigated by positron emission tomography, provide evidence for contextual integration not confined to the visual system. This supports the notion of common aspects of cortical computations in (...) different cerebral areas. (shrink)

The sounds that make up spoken words are heard in a series and must be mapped rapidly onto words in memory because their elements, unlike those of visual words, cannot simultaneously exist or persist in time. Although theories agree that the dynamics of spoken word recognition are important, they differ in how they treat the nature of the competitor set—precisely which words are activated as an auditory word form unfolds in real time. This study used eye tracking (...) to measure the impact over time of word frequency and 2 partially overlapping competitor set definitions: onset density and neighborhood density. Time course measures revealed early and continuous effects of frequency (facilitatory) and on set based similarity (inhibitory). Neighborhood density appears to have early facilitatory effects and late inhibitory effects. The late inhibitory effects are due to differences in the temporal distribution of similarity within neighborhoods. The early facilitatory effects are due to subphonemic cues that inform the listener about word length before the entire word is heard. The results support a new conception of lexical competition neighborhoods in which recognition occurs against a background of activated competitors that changes over time based on fine-grained goodness-of-fit and competition dynamics. (shrink)

This study examined the time-course of context effects on spoken word recognition during Chinese sentence processing. We recruited 60 native Mandarin listeners to participate in an eye-tracking experiment. In this eye-tracking experiment, listeners were told to listen to a sentence carefully, which ended with a Chinese homophone, and look at different visual probes presented concurrently on the computer screen naturally. Different types of context and probe types were manipulated in the experiment. The results showed that preceding sentence context (...) had an early effect on spoken word recognition processes and phonological information of the distracters had only a negligible effect on the spoken word recognition processes. Finally, the patterns of eye-tracking results seemed to favor an interactive approach in spoken word recognition. (shrink)

Most words in English are ambiguous between different interpretations; words can mean different things in different contexts. We investigate the implications of different types of semantic ambiguity for connectionist models of word recognition. We present a model in which there is competition to activate distributed semantic representations. The model performs well on the task of retrieving the different meanings of ambiguous words, and is able to simulate data reported by Rodd, Gaskell, and Marslen‐Wilson [J. Mem. Lang. 46 (2002) (...) 245] on how semantic ambiguity affects lexical decision performance. In particular, the network shows a disadvantage forwords with multiple unrelated meanings (e.g., bark) that coexists with a benefit for words with multiple related word senses (e.g., twist). The ambiguity disadvantage arises because of interference between the different meanings, while the sense benefit arises because of differences in the structure of the attractor basins formed during learning. Words with few senses develop deep, narrow attractor basins, while words with many senses develop shallow, broad basins. We conclude that the mental representations of word meanings can be modelled as stable states within a high‐dimensional semantic space, and that variations in the meanings of words shape the landscape of this space. (shrink)

Spoken communication occurs in a “noisy channel” characterized by high levels of environmental noise, variability within and between speakers, and lexical and syntactic ambiguity. Given these properties of the received linguistic input, robust spoken word recognition—and language processing more generally—relies heavily on listeners' prior knowledge to evaluate whether candidate interpretations of that input are more or less likely. Here we compare several broad-coverage probabilistic generative language models in their ability to capture human linguistic expectations. Serial reproduction, an experimental (...) paradigm where spoken utterances are reproduced by successive participants similar to the children's game of “Telephone,” is used to elicit a sample that reflects the linguistic expectations of English-speaking adults. When we evaluate a suite of probabilistic generative language models against the yielded chains of utterances, we find that those models that make use of abstract representations of preceding linguistic context (i.e., phrase structure) best predict the changes made by people in the course of serial reproduction. A logistic regression model predicting which words in an utterance are most likely to be lost or changed in the course of spoken transmission corroborates this result. We interpret these findings in light of research highlighting the interaction of memory-based constraints and representations in language processing. (shrink)

Frost proposes a new agenda for reading research, whereby cross-linguistic experiments would uncover linguistic universals to be integrated within a universal theory of reading. We reveal the dangers of following such a call, and demonstrate the superiority of the very approach that Frost condemns.

It has been recently argued that some machine learning techniques known as Kernel methods could be relevant for capturing cognitive and neural mechanisms (Jäkel, Schölkopf, & Wichmann, 2009). We point out that ‘‘String kernels,’’ initially designed for protein function prediction and spam detection, are virtually identical to one contending proposal for how the brain encodes orthographic information during reading. We suggest some reasons for this connection and we derive new ideas for visual word recognition that are successfully put (...) to the test. We argue that the versatility and performance of String kernels makes a compelling case for their implementation in the brain. (shrink)

A central component in the E-Z Reader model is a two-stage word processing mechanism made responsible for both the triggering of eye movements and sequential shifts of attention. We point to problems with both the verbal description of this mechanism and its computational implementation in the simulation. As an alternative, we consider the use of a connectionist processing module in combination with a more indirect form of cognitive eye-movement control.

The effects of psycholinguistic variables on reading development are critical to the evaluation of theories about the reading system. Although we know that the development of reading depends on both individual differences (endogenous) and item-level effects (exogenous), developmental research has focused mostly on average-level performance, ignoring individual differences. We investigated how the development of word recognition in Chinese children in both Chinese and English is affected by (a) item-level, exogenous effects (word frequency, radical consistency, and curricular grade (...) level); (b) subject-level, endogenous individual differences (orthographic awareness and phonological awareness); and (c) their interactive effect. We tested native Chinese (Putonghua)-speaking children (n = 763) in grades 1 to 6 with both Chinese character and English word identification (lexical) decision tasks. Our findings show that (a) there were effects of both word frequency and age of acquisition in both Chinese and English, but these item-level effects generally weakened with increasing age; (b) individual differences in phonological and orthographic awareness each contributed to successful performance; and (c) in Chinese, item-level effects were weaker for more proficient readers. We contend that our findings can be explained by theoretical models that incorporate cumulative learning as the basis for development of item-level effects in the reading system. (shrink)

Spoken word recognition involves a perceptual tradeoff between the reliance on the incoming acoustic signal and knowledge about likely sound categories and their co-occurrences as words. This study examined how adult second language (L2) learners navigate between acoustic-based and knowledge-based spoken word recognition when listening to highly variable, multi-talker truncated speech, and whether this perceptual tradeoff changes as L2 listeners gradually become more proficient in their L2 after multiple months of structured classroom learning. First language (L1) (...) Mandarin Chinese listeners and L1 English-L2 Mandarin adult listeners took part in a gating experiment. The L2 listeners were tested twice—once at the start of their intermediate/advanced L2 language class and again two months later. L1 listeners were only tested once. Participants were asked to identify syllable-tone words that varied in syllable token frequency (high/low according to a spoken word corpus) and syllable-conditioned tonal probability (most probable/least probable in speech given the syllable). The stimuli were recorded by 16 different talkers and presented at eight gates ranging from onset-only (gate 1) through onset+40 ms increments (gates 2 through 7) to the full word (gate 8). Mixed-effects regression modeling was used to compare performance to our previous study which used single-talker stimuli (Wiener, Lee, & Tao, 2019). The results indicated that multi-talker speech caused both L1 and L2 listeners to rely greater on knowledge-based processing of tone. L1 listeners were able to draw on distributional knowledge of syllable-tone probabilities in early gates and switch to predominantly acoustic-based processing when more of the signal was available. In contrast, L2 listeners, with their limited experience with talker range normalization, were less able to effectively transition from probability-based to acoustic-based processing. Moreover, for the L2 listeners, the reliance on such distributional information for spoken word recognition appeared to be conditioned by the nature of the acoustic signal. Single-talker speech did not result in the same pattern of probability-based tone processing, suggesting that knowledge-based processing of L2 speech may only occur under certain acoustic conditions, such as multi-talker speech. (shrink)

Unlike other writing systems that are readily classifiable as alphabetic or syllabic in their structure, the Indic Devanagari script (of which Hindi is an example) has properties of both syllabic and alphabetic writing systems. Whereas Devanagari consonants are written in a linear left-to-right order, vowel signs are positioned nonlinearly above, below, or to either side of the consonants. This fact results in certain words in Hindi for which, in a given syllable, the vowel precedes the consonant in writing but follows (...) it in speech. The current research exploited this property of the script to examine when the disparity between spatial and temporal sequenc- ing would incur a processing cost and the implications of the findings from naming speed, accuracy, and writing order for the level at which words in Devanagari are segmented. The results support a partly phonemic and partly syllabic level of segmentation, consistent with the structural hybridity of the script. (shrink)

Through computational modeling, here we examine whether visual and task characteristics of writing systems alone can account for lateralization differences in visual word recognition between different languages without assuming influence from left hemisphere (LH) lateralized language processes. We apply a hemispheric processing model of face recognition to visual word recognition; the model implements a theory of hemispheric asymmetry in perception that posits low spatial frequency biases in the right hemisphere and high spatial frequency (HSF) biases (...) in the LH. We show two factors that can influence lateralization: (a) Visual similarity among words: The more similar the words in the lexicon look visually, the more HSF/LH processing is required to distinguish them, and (b) Requirement to decompose words into graphemes for grapheme-phoneme mapping: Alphabetic reading (involving grapheme-phoneme conversion) requires more HSF/LH processing than logographic reading (no grapheme-phoneme mapping). These factors may explain the difference in lateralization between English and Chinese orthographic processing. (shrink)

Computational modelling has proven to be a valuable approach in developing theories of spoken-word processing. In this paper, we focus on a particular class of theories in which it is assumed that the spoken-word recognition process consists of two consecutive stages, with an `abstract' discrete symbolic representation at the interface between the stages. In evaluating computational models, it is important to bring in independent arguments for the cognitive plausibility of the algorithms that are selected to compute the (...) processes in a theory. This paper discusses the relation between behavioural studies, theories, and computational models of spoken-word recognition. We explain how computational models can be assessed in terms of the goodness of fit with the behavioural data and the cognitive plausibility of the algorithms. An in-depth analysis of several models provides insights into how computational modelling has led to improved theories and to a better understanding of the human spoken-word recognition process. (shrink)

Semantic priming has been a focus of research in the cognitive sciences for more than 30 years and is commonly used as a tool for investigating other aspects of perception and cognition, such as word recognition, language comprehension, and knowledge representations. Semantic Priming: Perspectives from Memory and Word Recognition examines empirical and theoretical advancements in the understanding of semantic priming, providing a succinct, in-depth review of this important phenomenon, framed in terms of models of memory and (...) models of word recognition. The first section examines models of semantic priming, including spreading activation models, the verification model, compound-cue models, distributed network models, and multistage activation models (e.g. interactive-activation model). The second section examines issues and findings that have played an especially important role in testing models of priming and includes chapters on the following topics: methodological issues (e.g. counterbalancing of materials, choice of priming baselines); automatic vs. strategic priming; associative vs. "pure" semantic priming; mediated priming; long-term semantic priming; backward priming; unconscious priming; the prime-task effect; list context effects; effects of word frequency, stimulus quality, and stimulus repetition; and the cognitive neuroscience of semantic priming. The book closes with a summary and a discussion of promising new research directions. The volume will be of interest to a wide range of researchers and students in the cognitive sciences and neurosciences. (shrink)

When reading, orthographic information is extracted not only from the word the reader is looking at, but also from adjacent words in the parafovea. Here we examined, using the recently introduced OB1‐reader computational model, how orthographic information can be processed in parallel across multiple words and how orthographic information can be integrated across time and space. Although OB1‐reader is a model of text reading, here we used it to simulate single‐word recognition experiments in which parallel processing has (...) been shown to play a role by manipulating the surrounding context in flanker and priming paradigms. In flanker paradigms, observers recognize a central word flanked by other letter strings located left and right of the target and separated from the target by a space. The model successfully accounts for the finding that such flankers can aid word recognition when they contain bigrams of the target word, independent of where those flankers are in the visual field. In priming experiments, in which the target word is preceded by a masked prime, the model accounts for the finding that priming occurs independent of whether the prime and target word are in the same location or not. Crucial to these successes is the key role that spatial attention plays within OB1‐reader, as it allows the model to receive visual input from multiple locations in parallel, while limiting the kinds of errors that can potentially occur under such spatial pooling of orthographic information. (shrink)

This study investigated the relative role of sub-syllabic components in spoken word recognition of Mandarin Chinese using an eye-tracking experiment with a visual world paradigm. Native Mandarin speakers were presented with four pictures and an auditory stimulus. They were required to click the picture according to the sound stimulus they heard, and their eye movements were tracked during this process. For a target word, nine conditions of competitors were constructed in terms of the amount of their phonological (...) overlap with the target: consonant competitor, rime competitor, tone competitor, consonant plus rime competitor, consonant plus tone competitor, rime plus tone competitor, cohort competitor, cohort plus tone competitor, and baseline competitor. A growth curve analysis was conducted with the fixation to competitors, targets, and distractors, and the results showed that competitors with consonant or rime overlap can be adequately activated, while tone overlap plays a weaker role since additional tonal information can strengthen the competitive effect only when it was added to a candidate that already bears much phonological similarity with the target. Mandarin words are processed in an incremental way in the time course of word recognition since different partially overlapping competitors could be activated immediately; like the pattern found in English, both cohort and rime competitors were activated to compete for lexical activation, but these two competitors were not temporally distinctive and mainly differed in the size of their competitive effects. Generally, the gradation of activation based on the phonological similarity between target and candidates found in this study was in line with the continuous mapping models and may reflect a strategy of native speakers shaped by the informative characteristics of the interaction among different sub-syllabic components. (shrink)