6 resultados para alphabetic-language reading models

em Aston University Research Archive


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In this chapter we outline a sensory-linguistic approach to the, study of reading skill development. We call this a sensory-linguistic approach because the focus of interest is on the relationship between basic sensory processing skills and the ability to extract efficiently the orthographic and phonological information available in text during reading. Our review discusses how basic sensory processing deficits are associated with developmental dyslexia, and how these impairments may degrade word-decoding skills. We then review studies that demonstrate a more direct relationship between sensitivity to particular types of auditory and visual stimuli and the normal development of literacy skills. Specifically, we suggest that the phonological and orthographic skills engaged while reading are constrained by the ability to detect and discriminate dynamic stimuli in the auditory and visual systems respectively.

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Dyslexia (or reading disability) and specific language impairment (or SLI) are common childhood disorders that show considerable co-morbidity and diagnostic overlaps and have been suggested to share some genetic aetiology. Recently, genetic risk variants have been identified for SLI and dyslexia enabling the direct evaluation of possible shared genetic influences between these disorders. In this study we investigate the role of variants in these genes (namely MRPL19/C20RF3, ROBO1, DCDC2, KIAA0319, DYX1C1, CNTNAP2, ATP2C2 and CMIP) in the aetiology of SLI and dyslexia. We perform case–control and quantitative association analyses using measures of oral and written language skills in samples of SLI and dyslexic families and cases. We replicate association between KIAA0319 and DCDC2 and dyslexia and provide evidence to support a role for KIAA0319 in oral language ability. In addition, we find association between reading-related measures and variants in CNTNAP2 and CMIP in the SLI families.

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Dyslexia as a concept is defined and reviewed in a context of psychological, neurological and educational processes. In the present investigation these processes are recognised but emphasis is placed on dyslexia as a phenomenon of a written language system. The type of script system involved in the phenomenon is that of an alphabetic code representing phonological elements of language In script form related to meaning. The nature of this system is viewed In the light of current linguistic and psycholinguistic studies. These studies based as they are on an analysis of underlying written language structures provide a framework for examining the arbitrary and rule-governed system which a young child is expected to acquire. There appear to be fundamental implications for reading, spelling and writing processes; for example an alphabetic system requires recognition of consistent script-phonetic relationships, 'mediated word identification' and in particular uni-directional sensory and motor modes of perceiving. These are critical maturational factors in the young learner. The skills needed by the child for decoding and encoding such a phonemic script are described in a psychological and neuropsychological framework. Evidence for individual differences in these skills is noted and the category of the dyslexic-type learner emerges. Incidence is related to the probabilities of individual differences in lateralisation of brain function not favouring the acquisition of our script system In some cases. Dyslexia is therefore regarded as a primary difficulty consequent upon the incompatibility between:the written language system itself and the intrinsic, developmental skills of an individual's perceptual/motor system. It is recognised that secondary stresses e.g. socio-cultural deprivation, low intellectual potential or emotional trauma can further inhibit the learning process. Symptomology of a dyslexic syndrome is described.. The symptomology is seen by the writer to constitute a clinical entity. a specific category of learning difficulty for which predictive and diagnostic procedure could be devised for classroom use. Consequently an index of relevant test items has been compiled, based upon key clinical experiences and theoretical writings. This instrument knovn as the Aston Index is presented and discussed. The early stages of validation are reported and the proposed longtitudinal studies are described. The aim is to give teachers in the classroom the power and understanding to plan more effectively the earliest stages of teaching and learning; in particular to provide the means of matching the nature of the skill to be acquired with the underlying developmental patterns of each individual learner.

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Purpose: Phonological accounts of reading implicate three aspects of phonological awareness tasks that underlie the relationship with reading; a) the language-based nature of the stimuli (words or nonwords), b) the verbal nature of the response, and c) the complexity of the stimuli (words can be segmented into units of speech). Yet, it is uncertain which task characteristics are most important as they are typically confounded. By systematically varying response-type and stimulus complexity across speech and non-speech stimuli, the current study seeks to isolate the characteristics of phonological awareness tasks that drive the prediction of early reading. Method: Four sets of tasks were created; tone stimuli (simple non-speech) requiring a non-verbal response, phonemes (simple speech) requiring a non-verbal response, phonemes requiring a verbal response, and nonwords (complex speech) requiring a verbal response. Tasks were administered to 570 2nd grade children along with standardized tests of reading and non-verbal IQ. Results: Three structural equation models comparing matched sets of tasks were built. Each model consisted of two 'task' factors with a direct link to a reading factor. The following factors predicted unique variance in reading: a) simple speech and non-speech stimuli, b) simple speech requiring a verbal response but not simple speech requiring a non-verbal-response, and c) complex and simple speech stimuli. Conclusions: Results suggest that the prediction of reading by phonological tasks is driven by the verbal nature of the response and not the complexity or 'speechness' of the stimuli. Findings highlight the importance of phonological output processes to early reading.

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Reading and language abilities are heritable traits that are likely to share some genetic influences with each other. To identify pleiotropic genetic variants affecting these traits, we first performed a genome-wide association scan (GWAS) meta-analysis using three richly characterized datasets comprising individuals with histories of reading or language problems, and their siblings. GWAS was performed in a total of 1862 participants using the first principal component computed from several quantitative measures of reading- and language-related abilities, both before and after adjustment for performance IQ. We identified novel suggestive associations at the SNPs rs59197085 and rs5995177 (uncorrected P≈10 for each SNP), located respectively at the CCDC136/FLNC and RBFOX2 genes. Each of these SNPs then showed evidence for effects across multiple reading and language traits in univariate association testing against the individual traits. FLNC encodes a structural protein involved in cytoskeleton remodelling, while RBFOX2 is an important regulator of alternative splicing in neurons. The CCDC136/FLNC locus showed association with a comparable reading/language measure in an independent sample of 6434 participants from the general population, although involving distinct alleles of the associated SNP. Our datasets will form an important part of on-going international efforts to identify genes contributing to reading and language skills. Genome-wide association scan meta-analysis for reading and language ability. © 2014 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

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Natural language understanding is to specify a computational model that maps sentences to their semantic mean representation. In this paper, we propose a novel framework to train the statistical models without using expensive fully annotated data. In particular, the input of our framework is a set of sentences labeled with abstract semantic annotations. These annotations encode the underlying embedded semantic structural relations without explicit word/semantic tag alignment. The proposed framework can automatically induce derivation rules that map sentences to their semantic meaning representations. The learning framework is applied on two statistical models, the conditional random fields (CRFs) and the hidden Markov support vector machines (HM-SVMs). Our experimental results on the DARPA communicator data show that both CRFs and HM-SVMs outperform the baseline approach, previously proposed hidden vector state (HVS) model which is also trained on abstract semantic annotations. In addition, the proposed framework shows superior performance than two other baseline approaches, a hybrid framework combining HVS and HM-SVMs and discriminative training of HVS, with a relative error reduction rate of about 25% and 15% being achieved in F-measure.