1,720,990 research outputs found
Causal modelling of developmental disorders: Insights from animal and computational models of Specific Language Impairment
No full textIn this chapter, we discuss the use of animal and computational models to gain a better understanding of the causes of developmental disorders. Both types of models provide a framework to study causal links between deficits observed at different levels of description. Here, we focus on language acquisition and Specific Language Impairment. We highlight the importance of model systems in supporting aetiological theories of atypical language development with mechanistic explanation
The Effects of Background Noise on Native and Non-native Spoken-word Recognition:A Computational Modelling Approach
Full text linkHow does the presence of background noise affect the cognitive processes underlying spoken-word recognition? And how do these effects differ in native and non-native language listeners? We addressed these questions using artificial neural-network modelling. We trained a deep auto-encoder architecture on binary phonological and semantic representations of 121 English and Dutch translation equivalents. We also varied exposure to the two languages to generate ‘native English’ and ‘non-native English’ trained networks. These networks captured key effects in the performance (accuracy rates and the number of erroneous responses per word stimulus) of English and Dutch listeners in an offline English spoken-word identification experiment (Scharenborg et al., 2017), which considered clean and noisy listening conditions and three intensities of speech-shaped noise, applied word-initially or word-finally. Our simulations suggested that the effects of noise on native and non-native listening are comparable and can be accounted for within the same cognitive architecture for spoken-word recognition
The relationship between SLI in English and Modern Greek: Insights from computational models of language acquisition
No full textWe present a computational modelling approach to the study of SLI in two languages with different typological characteristics, namely English and Modern Greek. Our modelling approach was based on the development of three neural network (connectionist) architectures, each assumed to underlie the acquisition of a core domain of language (inflectional morphology, syntax comprehension, and syntax production). The architectures were exposed to artificial linguistic environments reflecting the characteristics of their target domains in English and Greek. Computational simulations also considered conditions of atypical learning constraints, corresponding to different theoretical proposals for the type of deficit underlying SLI. The simulation results, combined with some shared properties of the three models, point to a unified explanation of the impairment under the connectionist framework
The Effects of Background Noise on Native and Non-native Spoken-word Recognition:A Computational Modelling Approach
Full text linkHow does the presence of background noise affect the cognitive processes underlying spoken-word recognition? And how do these effects differ in native and non-native language listeners? We addressed these questions using artificial neural-network modelling. We trained a deep auto-encoder architecture on binary phonological and semantic representations of 121 English and Dutch translation equivalents. We also varied exposure to the two languages to generate ‘native English’ and ‘non-native English’ trained networks. These networks captured key effects in the performance (accuracy rates and the number of erroneous responses per word stimulus) of English and Dutch listeners in an offline English spoken-word identification experiment (Scharenborg et al., 2017), which considered clean and noisy listening conditions and three intensities of speech-shaped noise, applied word-initially or word-finally. Our simulations suggested that the effects of noise on native and non-native listening are comparable and can be accounted for within the same cognitive architecture for spoken-word recognition
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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