scholarly journals Syntactic satiation and the inversion effect in English and Spanish wh-questions

2021 ◽  
pp. 216-235
Author(s):  
Grant Goodall
Keyword(s):  
Inversion Effect ◽  
Wh Questions

Responses of Language-Disordered Children to Wh-Questions

1986 ◽  
Vol 17 (2) ◽  
pp. 95-106 ◽  
Author(s):  
Martha M. Parnell ◽  
James D. Amerman ◽  
Roger D. Harting
Keyword(s):  
Relative Difficulty ◽  
Normal Children ◽  
Cognitive Linguistic ◽  
Wh Questions

Nineteen language-disordered children aged 3—7 years responded to items representing nine wh-question forms. Questions referred to three types of referential sources based on immediacy and visual availability. Three and 4-year-olds produced significantly fewer functionally appropriate and functionally accurate answers than did the 5- and 6-year-olds. Generally, questions asked with reference to nonobservable persons, actions, or objects appeared the most difficult. Why, when, and what happened questions were the most difficult of the nine wh-forms. In comparison with previous data from normal children, the language-disordered subjects' responses were significantly less appropriate and accurate. The language-disordered children also appeared particularly vulnerable to the increased cognitive/linguistic demands of questioning directed toward nonimmediate referents. A hierarchy of wh-question forms by relative difficulty was very similar to that observed for normal children. Implications for wh-question assessment and intervention are discussed.

Face Inversion Effect Emerges Under Critical Configural Discrepancy

2010 ◽  
Vol 69 (3) ◽  
pp. 161-167 ◽  
Author(s):  
Jisien Yang ◽  
Adrian Schwaninger
Keyword(s):  
Face Recognition ◽  
Face Processing ◽  
Underlying Mechanism ◽  
Inversion Effect ◽  
Configural Processing ◽  
Major Contributor ◽  
Face Inversion Effect ◽  
Configural Information ◽  
Face Inversion ◽  
The Face

Configural processing has been considered the major contributor to the face inversion effect (FIE) in face recognition. However, most researchers have only obtained the FIE with one specific ratio of configural alteration. It remains unclear whether the ratio of configural alteration itself can mediate the occurrence of the FIE. We aimed to clarify this issue by manipulating the configural information parametrically using six different ratios, ranging from 4% to 24%. Participants were asked to judge whether a pair of faces were entirely identical or different. The paired faces that were to be compared were presented either simultaneously (Experiment 1) or sequentially (Experiment 2). Both experiments revealed that the FIE was observed only when the ratio of configural alteration was in the intermediate range. These results indicate that even though the FIE has been frequently adopted as an index to examine the underlying mechanism of face processing, the emergence of the FIE is not robust with any configural alteration but dependent on the ratio of configural alteration.

Should we regard question-based media headlines as clickbait?

English Today ◽  
2021 ◽  
pp. 1-6
Author(s):  
Brian Poole
Keyword(s):  
Question Mark ◽  
Link Type ◽  
Wh Questions

In an article published a little over a decade ago (Betteridge, 2009), the journalist Ian Betteridge offered some scathing comments about a piece published a few days earlier in TechCrunch by Erick Schonfeld (Schonfeld, 2009). Amongst other things, Betteridge suggested that the headline concerned (‘Did Last.fm Just Hand Over User Listening Data to the RIAA?’) was ‘a great demonstration of my maxim that any headline which ends in a question mark can be answered by the word “no”.’ Readers of English Today will realise immediately that this ‘maxim’ cannot possibly be watertight as expressed by Betteridge, since only polar questions can be answered with a ‘yes’ or ‘no’. For example, WH-questions (Quirk & Greenbaum, 1973: 196) such as ‘Who opened my letter?’ and ‘How long have you been waiting?’ obviously cannot be responded to in any sensible way with a simple ‘yes’ or ‘no’. Furthermore, it is not difficult to find media headlines taking the form of non-polar questions: for example, “What would a no-deal Brexit mean for business?” (O'Dwyer et.al., 2020).

scholarly journals Research on Inversion Mechanism of Chlorophyll—A Concentration in Water Bodies Using a Convolutional Neural Network Model

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 664
Author(s):  
Yun Xue ◽  
Lei Zhu ◽  
Bin Zou ◽  
Yi-min Wen ◽  
Yue-hong Long ◽  
...  
Keyword(s):  
Neural Network ◽  
Regression Model ◽  
Convolutional Neural Network ◽  
Chlorophyll A ◽  
Language Processing ◽  
Water Bodies ◽  
Inversion Effect ◽  
Least Squares Regression ◽  
Chlorophyll A Concentration ◽  
Chl A

For Case-II water bodies with relatively complex water qualities, it is challenging to establish a chlorophyll-a concentration (Chl-a concentration) inversion model with strong applicability and high accuracy. Convolutional Neural Network (CNN) shows excellent performance in image target recognition and natural language processing. However, there little research exists on the inversion of Chl-a concentration in water using convolutional neural networks. Taking China’s Dongting Lake as an example, 90 water samples and their spectra were collected in this study. Using eight combinations as independent variables and Chl-a concentration as the dependent variable, a CNN model was constructed to invert Chl-a concentration. The results showed that: (1) The CNN model of the original spectrum has a worse inversion effect than the CNN model of the preprocessed spectrum. The determination coefficient (RP2) of the predicted sample is increased from 0.79 to 0.88, and the root mean square error (RMSEP) of the predicted sample is reduced from 0.61 to 0.49, indicating that preprocessing can significantly improve the inversion effect of the model.; (2) among the combined models, the CNN model with Baseline1_SC (strong correlation factor of 500–750 nm baseline) has the best effect, with RP2 reaching 0.90 and RMSEP only 0.45. The average inversion effect of the eight CNN models is better. The average RP2 reaches 0.86 and the RMSEP is only 0.52, indicating the feasibility of applying CNN to Chl-a concentration inversion modeling; (3) the performance of the CNN model (Baseline1_SC (RP2 = 0.90, RMSEP = 0.45)) was far better than the traditional model of the same combination, i.e., the linear regression model (RP2 = 0.61, RMSEP = 0.72) and partial least squares regression model (Baseline1_SC (RP2 = 0.58. RMSEP = 0.95)), indicating the superiority of the convolutional neural network inversion modeling of water body Chl-a concentration.

scholarly journals Coconuts and curtain cakes: The production of wh-questions in ASD

2021 ◽  
Vol 6 ◽  
pp. 239694152098295
Author(s):  
Nufar Sukenik ◽  
Eléonore Morin ◽  
Naama Friedmann ◽  
Philippe Prevost ◽  
Laurice Tuller
Keyword(s):  
Error Analysis ◽  
Language Disorder ◽  
Syntactic Structure ◽  
Autism Spectrum ◽  
Production Rates ◽  
Fine Grained ◽  
Depth Analysis ◽  
Wh Questions ◽  
Analysis Of Error ◽  
Error Types

Background and aims Children with autism spectrum disorders (ASD) have been found to exhibit difficulties in wh-question production. It is unclear whether these difficulties are pragmatic or syntactic in nature. The current study used a question elicitation task to assess the production of subject and object wh-questions of children with ASD in two different languages (Hebrew and French) wherein the syntactic structure of wh-questions is different, a fact that may contribute to better understanding of the underlying deficits affecting wh-question production. Crucially, beyond the general correct/error rate we also performed an in-depth analysis of error types, comparing syntactic to pragmatic errors and comparing the distribution of errors in the ASD group to that of children with typical development (TD) and children with Developmental Language Disorder (DLD). Results Correct production rates were found to be similar for the ASD and DLD groups, but error analysis revealed important differences between the ASD groups in the two languages and the DLD group. The Hebrew- and French ASD groups were found to produce pragmatic errors, which were not found in children with DLD. The pragmatic errors were similar in the two ASD groups. Syntactic errors were affected by the structure of each language. Conclusions Our results have shown that although the two ASD groups come from different countries and speak different languages, the correct production rates and more importantly, the error types were very similar in the two ASD groups, and very different compared to TD children and children with DLD. Implications: Our results highlight the importance of creating research tasks that test different linguistic functions independently and strengthen the need for conducting fine-grained error analysis to differentiate between groups and gain insights into the deficits underlying each of them.

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