Word reading and translation in bilinguals: the impact of formal and informal translation expertise

García, Adolfo M.; Ibáñez, Agustín; Huepe, David; Houck, Alexander L.; Michon, Maëva; Gelormini-Lezama, Carlos; Chadha, Sumeer; Rivera‐Rei, Álvaro

doi:10.3389/fpsyg.2014.01302

Cited by 26 publications

(42 citation statements)

References 59 publications

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“…3) were statistically significantly different (F (3,8) = 74.36, p < 0.001). For instance, the response time during C2E (47.29 ± 8.73 s) was the longest among the four conditions, followed by E2C (41.20 ± 7.92 s), E (24.82 ± 1.72 s), and C (21.19 ± 2.66 s).…”

Section: Behavioral Resultsmentioning

confidence: 97%

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Optical mapping of brain activation during the English to Chinese and Chinese to English sight translation

He¹,

Wang

Li³

et al. 2017

Biomed. Opt. Express

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Abstract:Translating from Chinese into another language or vice versa is becoming a widespread phenomenon. However, current neuroimaging studies are insufficient to reveal the neural mechanism underlying translation asymmetry during Chinese/English sight translation. In this study, functional near infrared spectroscopy (fNIRS) was used to extract the brain activation patterns associated with Chinese/English sight translation. Eleven unbalanced Chinese (L1)/English (L2) bilinguals participated in this study based on an intragroup experimental design, in which two translation and two reading aloud tasks were administered: forward translation (from L1 to L2), backward translation (from L2 to L1), L1 reading, and L2 reading. As predicted, our findings revealed that forward translation elicited more pronounced brain activation in Broca's area, suggesting that neural correlates of translation vary according to the direction of translation. Additionally, significant brain activation in the left PFC was involved in backward translation, indicating the importance of this brain region during the translation process. The identical activation patterns could not be discovered in forward translation, indicating the cognitive processing of reading logographic languages (i.e. Chinese) might recruit incongruent brain regions. References and links 1. J. F. Kroll and E. Stewart, "Category interference in translation and picture naming: Evidence for asymmetric connections between bilingual memory representations,"

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Section: Behavioral Resultsmentioning

confidence: 97%

“…Recent work has validated translation asymmetry, which is characterized as the asymmetrical levels of cognitive cost between forward translation (translating from L1 to L2) and backward translation (translating from L2 to L1) [1][2][3]. However, the neural correlates of translation have not been studied in depth.…”

Section: Introductionmentioning

confidence: 99%

Optical mapping of brain activation during the English to Chinese and Chinese to English sight translation

He¹,

Wang

Li³

et al. 2017

Biomed. Opt. Express

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“…However, the discussion of how interpreting experience modulates lexical processing and comprehension could also be enriched by findings from studies involving translators. García et al (2014) claim explicitly that strictly linguistic effects of translation experience may be independent of the modality, i.e., they would be similar in the case of interpreting and translation. This is juxtaposed with executive functions that might be more prone to change due to time constraints experienced by interpreters.…”

Section: Effects Of Training and Experience In Lexical Access And Commentioning

confidence: 97%

“…What follows is a review of lexical processing studies involving translators performing tasks that focused on comprehension. García et al (2014) studied word reading and word translation tasks performed by groups differing in translation experience: beginner translation trainees, advanced translation trainees and professional translators. They found that beginner trainees were significantly slower in general than translators and advanced trainees, while the latter two groups did not differ.…”

Section: Effects Of Training and Experience In Lexical Access And Commentioning

confidence: 99%

Meaning and words in the conference interpreter’s mind

Chmiel

2018

TCB

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The aim of the study was to examine how interpreter training and experience influence word recognition and cross-linguistic connections in the bilingual mental lexicon. Sixty-eight professional interpreters, interpreter trainees (tested at the beginning and end of their training) and bilingual controls were asked to complete a semantic priming study. Priming is a psycholinguistic research method used to examine connections between words and languages in the mind. Data analysis conducted by means of linear mixed models revealed that advanced trainees recognised words faster than beginners, but were not outperformed by professionals. A priming effect was found only in the L1-L2 direction, suggesting similar asymmetries between languages irrespective of the interpreting experience. It is the first study to adopt a priming paradigm and a longitudinal design to examine the interpreters’ mental lexicon. The study shows that word recognition is faster due to interpreter training, but is not modulated further by interpreting experience.

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“…We can summarize that these participants were truly multilingual and highly proficient. The degree of bilingualism is routinely reported in the literature because it has an effect on behaviour during translation [45].…”

Section: Participantsmentioning

confidence: 99%

Translation Quality and Error Recognition in Professional Neural Machine Translation Post-Editing

Vardaro¹,

Schaeffer²,

Hansen‐Schirra³

2019

Informatics

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This study aims to analyse how translation experts from the German department of the European Commission's Directorate-General for Translation (DGT) identify and correct different error categories in neural machine translated texts (NMT) and their post-edited versions (NMTPE). The term translation expert encompasses translator, post-editor as well as revisor. Even though we focus on neural machine-translated segments, translator and post-editor are used synonymously because of the combined workflow using CAT-Tools as well as machine translation. Only the distinction between post-editor, which refers to a DGT translation expert correcting the neural machine translation output, and revisor, which refers to a DGT translation expert correcting the post-edited version of the neural machine translation output, is important and made clear whenever relevant. Using an automatic error annotation tool and the more fine-grained manual error annotation framework to identify characteristic error categories in the DGT texts, a corpus analysis revealed that quality assurance measures by post-editors and revisors of the DGT are most often necessary for lexical errors. More specifically, the corpus analysis showed that, if post-editors correct mistranslations, terminology or stylistic errors in an NMT sentence, revisors are likely to correct the same error type in the same post-edited sentence, suggesting that the DGT experts were being primed by the NMT output. Subsequently, we designed a controlled eye-tracking and key-logging experiment to compare participants' eye movements for test sentences containing the three identified error categories (mistranslations, terminology or stylistic errors) and for control sentences without errors. We examined the three error types' effect on early (first fixation durations, first pass durations) and late eye movement measures (e.g., total reading time and regression path durations). Linear mixed-effects regression models predict what kind of behaviour of the DGT experts is associated with the correction of different error types during the post-editing process.Informatics 2019, 6, 41 2 of 29 the development of their own machine translation systems. Statistical machine translation (internally referred to as MT@EC) has been available at the DGT since 2013 and is now coming to an end. The new neural system, eTranslation, was launched in November 2017 and is able to "translate between any pair of the 24 official EU languages, as well as Icelandic and Norwegian (Bokmål): it can handle formatted documents and plain text; it translates multiple documents into multiple languages in "one go"; it accepts diverse input formats including XML and PDF; it retains formatting; and it provides specific output formats for computer-aided translation, i.e., TMX11 and XLIFF."It is trained with the aligned source and target segments that have been produced over the years-amounting to approximately 1.2 billion training segments ([1], p. 3).However, the usage of machine translation requires a different form of revisi...

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Word reading and translation in bilinguals: the impact of formal and informal translation expertise

Cited by 26 publications

References 59 publications

Optical mapping of brain activation during the English to Chinese and Chinese to English sight translation

Optical mapping of brain activation during the English to Chinese and Chinese to English sight translation

Meaning and words in the conference interpreter’s mind

Translation Quality and Error Recognition in Professional Neural Machine Translation Post-Editing

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