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Keith Rayner - One of the best experts on this subject based on the ideXlab platform.

  • the effect of Contextual Constraint on parafoveal processing in reading
    Journal of Memory and Language, 2015
    Co-Authors: Elizabeth R Schotter, Michael Reiderman, Keith Rayner
    Abstract:

    Semantic preview benefit in reading is an elusive and controversial effect because empirical studies do not always (but sometimes) find evidence for it. Its presence seems to depend on (at least) the language being read, visual properties of the text (e.g., initial letter capitalization), the type of relationship between preview and target, and as shown here, semantic Constraint generated by the prior sentence context. Schotter (2013) reported semantic preview benefit for synonyms, but not semantic associates when the preview/target was embedded in a neutral sentence context. In Experiment 1, we embedded those same previews/targets into constrained sentence contexts and in Experiment 2 we replicated the effects reported by Schotter (2013; in neutral sentence contexts) and Experiment 1 (in constrained contexts) in a within-subjects design. In both experiments, we found an early (i.e., first-pass) apparent preview benefit for semantically associated previews in constrained contexts that went away in late measures (e.g., total time). These data suggest that sentence Constraint (at least as manipulated in the current study) does not operate by making a single word form expected, but rather generates expectations about what kinds of words are likely to appear. Furthermore, these data are compatible with the assumption of the E-Z Reader model that early oculomotor decisions reflect “hedged bets” that a word will be identifiable and, when wrong, lead the system to identify the wrong word, triggering regressions.

  • Eye Movements and Word Skipping During Reading: Effects of Word Length and Predictability
    Journal of Experimental Psychology: Human Perception and Performance, 2011
    Co-Authors: Keith Rayner, Denis Drieghe, Timothy J. Slattery, Simon P. Liversedge
    Abstract:

    Eye movements were monitored as subjects read sentences containing high- or low-predictable target words. The extent to which target words were predictable from prior context was varied: Half of the target words were predictable, and the other half were unpredictable. In addition, the length of the target word varied: The target words were short (4–6 letters), medium (7–9 letters), or long (10–12 letters). Length and predictability both yielded strong effects on the probability of skipping the target words and on the amount of time readers fixated the target words (when they were not skipped). However, there was no interaction in any of the measures examined for either skipping or fixation time. The results demonstrate that word predictability (due to Contextual Constraint) and word length have strong and independent influences on word skipping and fixation durations. Furthermore, because the long words extended beyond the word identification span, the data indicate that skipping can occur on the basis of partial information in relation to word identity. (PsycINFO Database Record (c) 2012 APA, all rights reserved) (journal abstract)

  • the influence of parafoveal word length and Contextual Constraint on fixation durations and word skipping in reading
    Psychonomic Bulletin & Review, 2005
    Co-Authors: Sarah J White, Keith Rayner, Simon Paul Liversedge
    Abstract:

    The present study examined the relationship between the predictability of words within a sentence and the availability of parafoveal word length information, on when and where the eyes move in reading. Predictability influenced first-pass reading times when parafoveal word length preview information was correct, but not when it was incorrect. Similarly, for saccades launched from near the target word (wordn), predictability influenced the probability with which it was skipped only when the word length preview was correct. By contrast, for saccades launched farther away from wordn, predictability influenced word skipping regardless of the parafoveal word length preview. Taken together, the data suggest that parafoveal word length preview and predictability can act as a joint Constraint on the decision of when and where to move the eyes.

  • effects of Contextual Constraint on eye movements in reading a further examination
    Psychonomic Bulletin & Review, 1996
    Co-Authors: Keith Rayner, Arnold D Well
    Abstract:

    The effect of Contextual Constraint on eye movements in reading was examined by asking subjects to read sentences that contained a target word that varied in Contextual Constraint; high-, medium-, or low-Constraint target words were used. Subjects fixated low-Constraint target words longer than they did either high- or medium-Constraint target words. In addition, they skipped high-Constraint words more than they did either medium- or low-Constraint target words. The results further confirm that Contextual Constraint has a strong influence on eye movements during reading.

Gary Lupyan - One of the best experts on this subject based on the ideXlab platform.

  • Perspective taking in a novel signaling task: effects of world knowledge and Contextual Constraint
    2018
    Co-Authors: Justin Sulik, Gary Lupyan
    Abstract:

    Perspective taking - the ability to see things from someone else's point of view - can boost success in communication. A signaler might take perspective when designing an utterance that is informative from the receiver's point of view, or the receiver might take perspective when inferring the signaler's communicative intentions. Perspective taking is supposed to play a particularly vital role when people try to communicate in the absence of a conventional signaling system. However, the task demands in such cases are extremely different from those in typical experimental approaches to perspective taking. Thus, current evidence for perspective taking does not establish whether humans can take perspective in those cases where perspective taking is arguably most helpful. We describe experimental tests of perspective taking that are suitable for settling the matter. Our task focuses on the use of shared world knowledge rather than shared visual scenes, and it is suitable for both open-ended and Contextually constrained responses. We show that people generally fail at perspective taking in a novel signaling task, but that perspective taking can be boosted by Contextual Constraint. In that case, however, it is context, rather than perspective taking or shared world knowledge, that explains communicative success.

  • perspective taking in a novel signaling task effects of world knowledge and Contextual Constraint
    Journal of Experimental Psychology: General, 2018
    Co-Authors: Justin Sulik, Gary Lupyan
    Abstract:

    : Perspective taking-the ability to see things from someone else's point of view-can boost success in communication. A signaler might take perspective when designing an utterance that is informative from the receiver's point of view, or the receiver might take perspective when inferring the signaler's communicative intentions. Perspective taking is supposed to play a particularly vital role when people try to communicate in the absence of a conventional signaling system. However, the task demands in such cases are extremely different from those in typical experimental approaches to perspective taking. Thus, current evidence for perspective taking does not establish whether humans can take perspective in those cases where perspective taking is arguably most helpful. We describe experimental tests of perspective taking that are suitable for settling the matter. Our task focuses on the use of shared world knowledge rather than shared visual scenes, and it is suitable for both open-ended and Contextually constrained responses. We show that people generally fail at perspective taking in a novel signaling task, but that perspective taking can be boosted by Contextual Constraint. In that case, however, it is context, rather than perspective taking or shared world knowledge, that explains communicative success. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Simon Paul Liversedge - One of the best experts on this subject based on the ideXlab platform.

  • the influence of parafoveal word length and Contextual Constraint on fixation durations and word skipping in reading
    Psychonomic Bulletin & Review, 2005
    Co-Authors: Sarah J White, Keith Rayner, Simon Paul Liversedge
    Abstract:

    The present study examined the relationship between the predictability of words within a sentence and the availability of parafoveal word length information, on when and where the eyes move in reading. Predictability influenced first-pass reading times when parafoveal word length preview information was correct, but not when it was incorrect. Similarly, for saccades launched from near the target word (wordn), predictability influenced the probability with which it was skipped only when the word length preview was correct. By contrast, for saccades launched farther away from wordn, predictability influenced word skipping regardless of the parafoveal word length preview. Taken together, the data suggest that parafoveal word length preview and predictability can act as a joint Constraint on the decision of when and where to move the eyes.

Simon P. Liversedge - One of the best experts on this subject based on the ideXlab platform.

  • Eye Movements and Word Skipping During Reading: Effects of Word Length and Predictability
    Journal of Experimental Psychology: Human Perception and Performance, 2011
    Co-Authors: Keith Rayner, Denis Drieghe, Timothy J. Slattery, Simon P. Liversedge
    Abstract:

    Eye movements were monitored as subjects read sentences containing high- or low-predictable target words. The extent to which target words were predictable from prior context was varied: Half of the target words were predictable, and the other half were unpredictable. In addition, the length of the target word varied: The target words were short (4–6 letters), medium (7–9 letters), or long (10–12 letters). Length and predictability both yielded strong effects on the probability of skipping the target words and on the amount of time readers fixated the target words (when they were not skipped). However, there was no interaction in any of the measures examined for either skipping or fixation time. The results demonstrate that word predictability (due to Contextual Constraint) and word length have strong and independent influences on word skipping and fixation durations. Furthermore, because the long words extended beyond the word identification span, the data indicate that skipping can occur on the basis of partial information in relation to word identity. (PsycINFO Database Record (c) 2012 APA, all rights reserved) (journal abstract)

Pau-choo Chung - One of the best experts on this subject based on the ideXlab platform.

  • Knee MR image segmentation combining Contextual constrained neural network and level set evolution
    2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2009
    Co-Authors: Tsai-rong Chang, Wen-ching Liao, Yi-nun Chung, Pau-choo Chung
    Abstract:

    Tracking the patella movement trajectory during the bending process of the knee is one essential step to knee pain diagnosis. In order for tracking patella, correct segmentation of the femur and patella from the axial knee MR image is indispensable. But the strong adhesion of the soft tissue around femur and patella, the gray-level similarities of adjacent organs, and the non-uniform gray intensity due to the degradation of the magnetic propagation make the MR image segmentation challenging. In this paper, we proposed a mechanism combining Contextual Constraint neural network (CCNN) and level set evolution to segment the femur and patella. The segmentation can be divided into two phases. In the first phase SOM and CCNN are applied to extract initial contours of the femur and patella. Consequently in the second phase, modified level set evolution is performed, with the extracted contours as the initial zero level set contour, to accomplish the segmentation of the femur and patella. Our experimental results show that the femur and patella can be correctly segmented for tracking patella movement.

  • medical image segmentation using a Contextual Constraint based hopfield neural cube
    Image and Vision Computing, 2001
    Co-Authors: Chuan-yu Chang, Pau-choo Chung
    Abstract:

    Abstract Neural-network-based image techniques such as the Hopfield neural networks have been proposed as an alternative approach for image segmentation and have demonstrated benefits over traditional algorithms. However, due to its architecture limitation, image segmentation using traditional Hopfield neural networks results in the same function as thresholding of image histograms. With this technique high-level Contextual information cannot be incorporated into the segmentation procedure. As a result, although the traditional Hopfield neural network was capable of segmenting noiseless images, it lacks the capability of noise robustness. In this paper, an innovative Hopfield neural network, called Contextual-Constraint-based Hopfield neural cube (CCBHNC) is proposed for image segmentation. The CCBHNC uses a three-dimensional architecture with pixel classification implemented on its third dimension. With the three-dimensional architecture, the network is capable of taking into account each pixel's feature and its surrounding Contextual information. Besides the network architecture, the CCBHNC also differs from the original Hopfield neural network in that a competitive winner-take-all mechanism is imposed in the evolution of the network. The winner-take-all mechanism adeptly precludes the necessity of determining the values for the weighting factors for the hard Constraints in the energy function in maintaining feasible results. The proposed CCBHNC approach for image segmentation has been compared with two existing methods. The simulation results indicate that CCBHNC can produce more continuous, and smoother images in comparison with the other methods.

  • Recognizing abdominal organs in CT images using Contextual neural network and fuzzy rules
    Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Cat. No.00CH37143), 2000
    Co-Authors: Pau-choo Chung
    Abstract:

    This paper describes a method for automatic abdominal organ recognition from a series of CT image slices, that is based on shape analysis, image Contextual Constraint, and between-slice relationship. A Contextual neural network is applied to segment each image slice into disconnected regions. For each region, its shape features are calculated, along with its spatial relationships with respect to spine. Then, according to the knowledge of anatomy, these features are constructed to form fuzzy rules used for organ recognition. In the recognition process, the obtained features and the overlapping between adjacent slices are used for identifying each organ. This proposed method of recognizing organs has been successfully tested in several clinical cases.

  • A Contextual-Constraint based Hopfield neural cube for medical image segmentation
    Proceedings of IEEE. IEEE Region 10 Conference. TENCON 99. 'Multimedia Technology for Asia-Pacific Information Infrastructure' (Cat. No.99CH37030), 1999
    Co-Authors: Chuan-yu Chang, Pau-choo Chung
    Abstract:

    Proposes a 3-D Hopfield neural network called Contextual-Constraint Based Hopfield Neural Cube (CCBHNC) taking both each single pixel's feature and its surrounding Contextual information for image segmentation, mimicking a high-level vision system. Different from other neural networks, CCBHNC extends the two-dimensional Hopfield neural network into a three-dimensional Hopfield neural cube for it to easily take each pixel's surrounding Contextual information into its network operation. As CCBHNC uses a high-level image segmentation model, disconnected fractions arising in the course of tiny details or noises will be effectively removed. Furthermore, the CCBHNC follows the competitive learning rule to update the neuron states, thus precluding the necessity of determining the values for the hard Constraints in the energy function, which is usually required in a Hopfield neural network, and facilitating the energy function to converge fast. The simulation results indicate that CCBHNC can produce more continued, more intact, and smoother images in comparison with the other methods.