7 resultados para l1-regularized LSP

em Aston University Research Archive


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Our PhD study focuses on the role of aspectual marking in expressing simultaneity of events in Tunisian Arabic as a first language, French as a first language, as well as in French as a second language by Tunisian learners at different acquisitional stages. We examine how the explicit markers of on-goingness qa:’id and «en train de» in Tunisian Arabic and in French respectively are used to express this temporal relation, in competition with the simple forms, the prefixed verb form in Tunisian Arabic and the présent de l’indicatif in French. We use a complex verbal task of retelling simultaneous events sharing an interval on the time axis based on eight videos presenting two situations happening in parallel. Two types of simultaneity are exploited: perfect simultaneity (when the two situations are parallel to each other) and inclusion (one situation is framed by the second one). Our informants in French and in Tunisian Arabic have two profiles, highly educated and low educated speakers. We show that the participants’ response to the retelling task varies according to their profiles, and so does their use of the on-goingness devices in the expression of simultaneity. The differences observed between the two profile groups are explained by the degree to which the speakers have developed a habit of responding to tasks. This is a skill typically acquired during schooling. We notice overall that the use of qa:’id as well as of «en train de» is less frequent in the data than the use of the simple forms. However, qa:’id as well as «en train de» are employed to play discursive roles that go beyond the proposition level. We postulate that despite the shared features between Tunisian Arabic and French regarding marking the concept of on-goingness, namely the presence of explicit lexical, not fully grammaticalised markers competing with other non-marked forms, the way they are used in the discourse of simultaneous events shows clear differences. We explain that «en train de» plays a more contrastive role than qa:’id and its use in discourse obeys a stricter rule. In cases of the inclusion type of simultaneity, it is used to construe the ‘framing’ event that encloses the second event. In construing perfectly simultaneneous events, and when both «en train de» and présent de l’indicatif are used, the proposition with «en train de» generally precedes the proposition with présent de l’indicatif, and not the other way around. qa:id obeys, but to a less strict rule as it can be used interchangeably with the simple form regardless of the order of propositions. The contrastive analysis of French L1 and L2 reveals learners’ deviations from natives’ use of on-goingness devices. They generalise the use of «en train de» and apply different rules to the interaction of the different marked and unmarked forms in discourse. Learners do not master its role in discourse even at advanced stages of acquisition despite its possible emergence around the basic and intermediate varieties. We conclude that the native speakers’ use of «en train de» involves mastering its role at the macro-structure level. This feature, not explicitly available to learners in the input, might persistently present a challenge to L2 acquisition of the periphrasis.

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This article uncovers the complexities and contradictions inherent in making decisions about L1 use in the English language classroom. Through an analysis of data from classrooms in a Cypriot context and from interviews with Cypriot teachers, a number of functions for L1 use are identified, as are the teachers' rationales for using L1 for different functions. Teachers' decision making, it emerges, is often complex, based on either what they perceive as their students' affective needs or on their cognitive processes.What ismore, teachers often under-report or differently report their use of L1 in the classroom, contradicting beliefs by their actions. The construct of guilt is offered to explain these complexities and contradictions in the teachers' use of L1 in this study. We conclude by suggesting that teachers should be supported in finding local solutions to local teaching problems, so that they better understand and exploit the resources available to them. © The Author 2010. Published by Oxford University Press; all rights reserved.

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This research focuses on Native Language Identification (NLID), and in particular, on the linguistic identifiers of L1 Persian speakers writing in English. This project comprises three sub-studies; the first study devises a coding system to account for interlingual features present in a corpus of L1 Persian speakers blogging in English, and a corpus of L1 English blogs. Study One then demonstrates that it is possible to use interlingual identifiers to distinguish authorship by L1 Persian speakers. Study Two examines the coding system in relation to the L1 Persian corpus and a corpus of L1 Azeri and L1 Pashto speakers. The findings of this section indicate that the NLID method and features designed are able to discriminate between L1 influences from different languages. Study Three focuses on elicited data, in which participants were tasked with disguising their language to appear as L1 Persian speakers writing in English. This study indicated that there was a significant difference between the features in the L1 Persian corpus, and the corpus of disguise texts. The findings of this research indicate that NLID and the coding system devised have a very strong potential to aid forensic authorship analysis in investigative situations. Unlike existing research, this project focuses predominantly on blogs, as opposed to student data, making the findings more appropriate to forensic casework data.

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Master of Arts dissertation

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In this paper, we first present a simple but effective L1-norm-based two-dimensional principal component analysis (2DPCA). Traditional L2-norm-based least squares criterion is sensitive to outliers, while the newly proposed L1-norm 2DPCA is robust. Experimental results demonstrate its advantages. © 2006 IEEE.

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Tensor analysis plays an important role in modern image and vision computing problems. Most of the existing tensor analysis approaches are based on the Frobenius norm, which makes them sensitive to outliers. In this paper, we propose L1-norm-based tensor analysis (TPCA-L1), which is robust to outliers. Experimental results upon face and other datasets demonstrate the advantages of the proposed approach. © 2006 IEEE.