Automatic detection and correction of discourse marker errors made by Spanish native speakers in Portuguese academic writing.
Discourse markers are words and expressions (such as: firstly, then, for example, because, as a result, likewise, in comparison, in contrast) that explicitly state the relational structure of the information in the text, i.e. signalling a sequential relationship between the current message and the p...
| Publicado en: | Language Resources & Evaluation Vol. 53; no. 3; pp. 525 - 559 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Springer Nature
Sep2019
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=138297598&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 138297598 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Sep2019 vid: 53 iid: 3 pid: 237 pub: Springer Nature artinfo: ui: 138297598 10.1007/s10579-019-09467-3 ppf: 525 ppct: 34 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1MB tig: atl: Automatic detection and correction of discourse marker errors made by Spanish native speakers in Portuguese academic writing. aug: au: Sepúlveda-Torres, Lianet Sanches Duran, Magali Aluísio, Sandra Maria affil: Interinstitutional Center for Computational Linguistics (NILC), Institute of Mathematics and Computer Science, University of São Paulo, São Carlos, Brazil su: Discourse markers Native language Academic discourse Reading comprehension sug: subj: Discourse markers Native language Academic discourse Reading comprehension keyword: Academic writing Detection/correction of errors Native language interference Writing support tool ab: Discourse markers are words and expressions (such as: firstly, then, for example, because, as a result, likewise, in comparison, in contrast) that explicitly state the relational structure of the information in the text, i.e. signalling a sequential relationship between the current message and the previous discourse. Using these markers improves the cohesion and coherence of texts, facilitating reading comprehension. Although often included in tools that support the rhetoric structuring of texts, discourse markers have hardly been explored in writing support tools for learners of a second language. However, learners of a second language, including those at advanced levels, have trouble producing these lexical items, frequently replacing them with items from their native language or with literal translations of items in their own language, which often do not result in proper lexical items in the second language. In addition, students learn a single marker per function and use it repeatedly, producing monotonous texts. With the aim of contributing to reducing these difficulties, this paper presents a lexicon that will be used to support the task of automatically detecting and correcting discourse marker errors. Several heuristics have been evaluated to generate different types of errors. Automatic translation methods were used to semi-automatically compile the lexicon used in these heuristics. Similarity measures were also combined with these heuristics to correct discourse marker errors. The evaluated methods proved to be suitable for the task of identifying some types of discourse marker errors and can potentially identify many others, as long as new lexical inputs are incorporated into them. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2019. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2019 holdings: @attributes: islocal: N |
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