Post-editing strategies in automatic translation of proverbs by FFL and translation learners

Detalhes bibliográficos
Autor(a) principal: Kandeel, Rana
Data de Publicação: 2021
Tipo de documento: Artigo
Idioma: fra
Título da fonte: Texto livre
Texto Completo: https://periodicos.ufmg.br/index.php/textolivre/article/view/29459
Resumo: This research aims to analyze the strategies used in the post-editing of proverbs translated automatically from French into Arabic by French as a Foreign Language (FFL) learners. We first present the theoretical foundations of machine translation of proverbs as well as the state of the art. The study uses a mixed methodological approach. The quantitative method includes a questionnaire distributed for FFL students to find out the most used translation tool in machine translation. The qualitative method focuses on collecting data on translation errors as well as on directly observing the strategies implemented in the post-editing of proverbs translated by Google Translate. The results of the study show that Google Translate is the most widely used tool in translation and that errors in machine translation are syntactic, lexical, semantic, and stylistic. The strategies implemented in the post-edition are varied such as splitting proverbs into linguistic units for the search of their meanings, using a pivot language, namely English to know the meaning of proverbs and searching for equivalents in reference resources. The study concludes that although the automatic translation of proverbs into distant language pairs such as the French-Arabic pair appears complex, Google Translate has been a tool to help an FFL learner to understand the meaning of proverbial expressions, to find their equivalents and to post-edit them.
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spelling Post-editing strategies in automatic translation of proverbs by FFL and translation learnersLes stratégies de la post-édition en traduction automatique des proverbes par des apprenants FLE et de traductionEstratégias de pós-edição na tradução automática de provérbios por alunos da FLE e da traduçãoStratégiesProverbesTraduction automatiqueFrançais langue étrangèrePost-éditionStrategiesProverbsMachine translationFrench as a foreign languagePost-editionEstratégiasProvérbiosTradução automáticaFrancês como língua estrangeiraPós-ediçãoThis research aims to analyze the strategies used in the post-editing of proverbs translated automatically from French into Arabic by French as a Foreign Language (FFL) learners. We first present the theoretical foundations of machine translation of proverbs as well as the state of the art. The study uses a mixed methodological approach. The quantitative method includes a questionnaire distributed for FFL students to find out the most used translation tool in machine translation. The qualitative method focuses on collecting data on translation errors as well as on directly observing the strategies implemented in the post-editing of proverbs translated by Google Translate. The results of the study show that Google Translate is the most widely used tool in translation and that errors in machine translation are syntactic, lexical, semantic, and stylistic. The strategies implemented in the post-edition are varied such as splitting proverbs into linguistic units for the search of their meanings, using a pivot language, namely English to know the meaning of proverbs and searching for equivalents in reference resources. The study concludes that although the automatic translation of proverbs into distant language pairs such as the French-Arabic pair appears complex, Google Translate has been a tool to help an FFL learner to understand the meaning of proverbial expressions, to find their equivalents and to post-edit them.Cette recherche a pour objectif d’analyser les stratégies utilisées dans la post-édition des proverbes traduits automatiquement du français en arabe par des apprenants du Français Langue Étrangère (FLE). Nous présenterons d’abord les fondements théoriques de la traduction automatique des proverbes ainsi que l’état de l’art. L’étude utilise une approche méthodologique mixte. La méthode quantitative comprend un questionnaire distribué sur les étudiantes de FLE pour connaître l’outil de traduction le plus utilisé dans la traduction automatique. La méthode qualitative est axée sur la collecte des données concernant les erreurs de traduction ainsi que sur l’observation directe des stratégies mises en œuvre dans la post-édition de proverbes traduits par Google Translate. Les résultats de l’étude montrent que Google Translate est l’outil le plus utilisé en traduction et que les erreurs de traduction automatique sont d’ordre syntaxique, lexical, sémantique et stylistique. Les stratégies mises en œuvre dans la post-édition sont variées : découpage des proverbes en unités linguistiques pour la recherche de sens, recours à une langue-pivot (l’anglais), et recherche des équivalents dans des ressources de référence. L’étude conclut que bien que la traduction automatique des proverbes dans les paires de langues éloignées telles que le français et l’arabe semble complexe, Google Translate a constitué un outil d’aide à la compréhension des mots constitutifs des proverbes pour des apprenants FLE, ce qui a permis la compréhension du sens des expressions proverbiales, de trouver leurs équivalents et de les post-éditer.Essa pesquisa pretende analisar as estratégias usadas na pós-edição de provérbios traduzidos automaticamente do francês para o árabe pelo Francês como Língua Estrangeira (FLE). Apresentaremos primeiro as bases teóricas da tradução automática de provérbios e, em seguida, o estado da arte. O estudo utiliza uma abordagem metodológica mista. O método quantitativo inclui um questionário distribuído aos estudantes de FLE para descobrir a ferramenta de tradução mais usada na tradução automática. O método qualitativo se concentra na coleta de dados sobre erros de tradução, bem como na observação direta das estratégias implementadas na pós-edição de provérbios traduzidos pelo Google Tradutor. Os resultados do estudo mostram que o Google Tradutor é a ferramenta mais usada na tradução e que os erros na tradução automática são sintáticos, léxicos, semânticos e estilísticos. As estratégias implementadas na pós-edição são variadas, como dividir provérbios em unidades linguísticas para a busca de seus significados, usando uma linguagem pivô, o inglês, para conhecer o significado de provérbios e buscar equivalentes em recursos de referência. O estudo conclui que, embora a tradução automática de provérbios em pares de idiomas distantes, como o par franco-árabe, pareça complexa, o Google Tradutor tem sido uma ferramenta para ajudar um aprendiz de FLE a entender o significado de expressões proverbiais, a encontrar seus equivalentes e a pós-editá-los.Universidade Federal de Minas Gerais2021-08-13info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtigo avaliado pelos paresapplication/pdfhttps://periodicos.ufmg.br/index.php/textolivre/article/view/2945910.35699/1983-3652.2021.29459Texto Livre; Vol. 14 No. 3 (2021): Texto Livre: Linguagem e Tecnologia; e29459Texto Livre; Vol. 14 Núm. 3 (2021): Texto Livre: Linguagem e Tecnologia; e29459Texto Livre; Vol. 14 No 3 (2021): Texto Livre: Linguagem e Tecnologia; e29459Texto Livre; v. 14 n. 3 (2021): Texto Livre: Linguagem e Tecnologia; e294591983-3652reponame:Texto livreinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGfrahttps://periodicos.ufmg.br/index.php/textolivre/article/view/29459/28021Copyright (c) 2021 Texto Livre: Linguagem e Tecnologiahttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessKandeel, Rana2022-03-24T11:05:56Zoai:periodicos.ufmg.br:article/29459Revistahttp://www.periodicos.letras.ufmg.br/index.php/textolivrePUBhttps://periodicos.ufmg.br/index.php/textolivre/oairevistatextolivre@letras.ufmg.br1983-36521983-3652opendoar:2022-03-24T11:05:56Texto livre - Universidade Federal de Minas Gerais (UFMG)false
dc.title.none.fl_str_mv Post-editing strategies in automatic translation of proverbs by FFL and translation learners
Les stratégies de la post-édition en traduction automatique des proverbes par des apprenants FLE et de traduction
Estratégias de pós-edição na tradução automática de provérbios por alunos da FLE e da tradução
title Post-editing strategies in automatic translation of proverbs by FFL and translation learners
spellingShingle Post-editing strategies in automatic translation of proverbs by FFL and translation learners
Kandeel, Rana
Stratégies
Proverbes
Traduction automatique
Français langue étrangère
Post-édition
Strategies
Proverbs
Machine translation
French as a foreign language
Post-edition
Estratégias
Provérbios
Tradução automática
Francês como língua estrangeira
Pós-edição
title_short Post-editing strategies in automatic translation of proverbs by FFL and translation learners
title_full Post-editing strategies in automatic translation of proverbs by FFL and translation learners
title_fullStr Post-editing strategies in automatic translation of proverbs by FFL and translation learners
title_full_unstemmed Post-editing strategies in automatic translation of proverbs by FFL and translation learners
title_sort Post-editing strategies in automatic translation of proverbs by FFL and translation learners
author Kandeel, Rana
author_facet Kandeel, Rana
author_role author
dc.contributor.author.fl_str_mv Kandeel, Rana
dc.subject.por.fl_str_mv Stratégies
Proverbes
Traduction automatique
Français langue étrangère
Post-édition
Strategies
Proverbs
Machine translation
French as a foreign language
Post-edition
Estratégias
Provérbios
Tradução automática
Francês como língua estrangeira
Pós-edição
topic Stratégies
Proverbes
Traduction automatique
Français langue étrangère
Post-édition
Strategies
Proverbs
Machine translation
French as a foreign language
Post-edition
Estratégias
Provérbios
Tradução automática
Francês como língua estrangeira
Pós-edição
description This research aims to analyze the strategies used in the post-editing of proverbs translated automatically from French into Arabic by French as a Foreign Language (FFL) learners. We first present the theoretical foundations of machine translation of proverbs as well as the state of the art. The study uses a mixed methodological approach. The quantitative method includes a questionnaire distributed for FFL students to find out the most used translation tool in machine translation. The qualitative method focuses on collecting data on translation errors as well as on directly observing the strategies implemented in the post-editing of proverbs translated by Google Translate. The results of the study show that Google Translate is the most widely used tool in translation and that errors in machine translation are syntactic, lexical, semantic, and stylistic. The strategies implemented in the post-edition are varied such as splitting proverbs into linguistic units for the search of their meanings, using a pivot language, namely English to know the meaning of proverbs and searching for equivalents in reference resources. The study concludes that although the automatic translation of proverbs into distant language pairs such as the French-Arabic pair appears complex, Google Translate has been a tool to help an FFL learner to understand the meaning of proverbial expressions, to find their equivalents and to post-edit them.
publishDate 2021
dc.date.none.fl_str_mv 2021-08-13
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Artigo avaliado pelos pares
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.ufmg.br/index.php/textolivre/article/view/29459
10.35699/1983-3652.2021.29459
url https://periodicos.ufmg.br/index.php/textolivre/article/view/29459
identifier_str_mv 10.35699/1983-3652.2021.29459
dc.language.iso.fl_str_mv fra
language fra
dc.relation.none.fl_str_mv https://periodicos.ufmg.br/index.php/textolivre/article/view/29459/28021
dc.rights.driver.fl_str_mv Copyright (c) 2021 Texto Livre: Linguagem e Tecnologia
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 Texto Livre: Linguagem e Tecnologia
https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Minas Gerais
publisher.none.fl_str_mv Universidade Federal de Minas Gerais
dc.source.none.fl_str_mv Texto Livre; Vol. 14 No. 3 (2021): Texto Livre: Linguagem e Tecnologia; e29459
Texto Livre; Vol. 14 Núm. 3 (2021): Texto Livre: Linguagem e Tecnologia; e29459
Texto Livre; Vol. 14 No 3 (2021): Texto Livre: Linguagem e Tecnologia; e29459
Texto Livre; v. 14 n. 3 (2021): Texto Livre: Linguagem e Tecnologia; e29459
1983-3652
reponame:Texto livre
instname:Universidade Federal de Minas Gerais (UFMG)
instacron:UFMG
instname_str Universidade Federal de Minas Gerais (UFMG)
instacron_str UFMG
institution UFMG
reponame_str Texto livre
collection Texto livre
repository.name.fl_str_mv Texto livre - Universidade Federal de Minas Gerais (UFMG)
repository.mail.fl_str_mv revistatextolivre@letras.ufmg.br
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