An Approach for Identifying Problem-Solving Activities in Post-Editing and Translation From Scratch

Nitzke, Jean

doi:10.4324/9780429030376-5

Cited by 13 publications

(18 citation statements)

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“…Due to the rapid development of translation technology, particularly machine translations, therefore, it is important for the student translators to consider whether or not a certain type of text should be translated by human translators. As the alternative, the text could actually be machine translated as its initial draft and post-edited it to meet the required quality, full post-editing (Full PE), in which the text is intended for publication, or light post-editing (Light PE) in which the text is for gisting (Koglin & Cunha, 2019;Nitzke, 2019;Nitzke et al, 2019;Sin-wai, 2017;Vieira et al, 2019). The importance of understanding translation technology, a future-use of translation technology (Schaler et al, 2003;in Quah, 2006) presented in Figure 1 above aims to provide students and translators with some information and guidelines to decide whether a particular text type was supposed to be translated from scratch.…”

Section: Figurementioning

confidence: 99%

Exploring undergraduate students’ experiences in dealing with post-editing of machine translation

Harto

Hamied

Musthafa

et al. 2022

Indonesian J. Appl. Linguist.

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Although post-editing of machine translation (PEMT) has been much discussed and spoken among students in higher education institutions, little empirical evidence has been reported regarding the students’ real practices in their academic life. To fill this practical gap, this article explores the students’ experiences in dealing with PEMT in a Theoretical Foundation of Translating and Interpreting (TFTI) course. This exploration elaborates practical insights into how the students initially started practicing translation through PEMT in their actual day-to-day practices. Fifty-eight English students studying in an undergraduate program in a prominent public university in Indonesia voluntarily participated in this qualitative case study. Data were collected from students’ focused-group discussion (FGD), survey questionnaire, in-depth interviews, and students’ documents and the data were analyzed using thematic analysis. Findings showed that post-editing process provides the students with experiences in building their text knowledge to enable them to have high awareness and sensitivity to the academic texts. In addition, in PEMT practices, the students’ experiences were explored through the implementation of translation methods and techniques expected to build their awareness in PEMT with regard to language structure and language function. These experiences have given some empirical inputs for the lecturers to design relevant tasks and apply various translating practices for students’ more meaningful learning.

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Section: Figurementioning

confidence: 99%

Exploring undergraduate students’ experiences in dealing with post-editing of machine translation

Harto

Hamied

Musthafa

et al. 2022

Indonesian J. Appl. Linguist.

View full text Add to dashboard Cite

show abstract

“…“Bad” machine translation is still unproductive, on the contrary, “good” machine translation can make post-editors’ work easier and thus increase their productivity. Researchers examining post-editing in MT agree that PE can increase productivity in terms of speed and sometimes in quality of the translation (Bangalore et al, 2015; Nitzke, 2019; O’Brien et al, 2014). Daems et al (2017) carried out a test with eight professional translators and 10 students of translation studies, they found that post-editing of newspaper texts was significantly faster than translation from scratch.…”

Section: Discussionmentioning

confidence: 99%

Product and Process Analysis of Machine Translation into the Inflectional Language

et al. 2021

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This study focuses on the influence of quality of Machine Translation (MT) output on a translator’s performance. We analyze the translator’s effort by product analysis and process analysis. The product analysis consists of MT quality evaluation according to the Dynamic Quality Framework; using error typology and the criteria such as fluency and adequacy. We examine translator’s effort from the point of view of typing time, in the context of MT quality—focusing on error rate in language, accuracy, terminology, and style, and also in fluency and adequacy to the source text. We have found that the translator’s performance is influenced by MT quality. The typing time is very closely related to errors in language, accuracy, terminology, and style as well as to fluency and adequacy. We used the Mann-Whitney test to compare the productivity of post-editing of MT with human translation. The results of the study have shown that post-editing—compared to human translation of journalistic text from English into the inflectional Slovak language is more effective.

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“…Cilj je prethodnom detekcijom i prilagodbom/modifikacijom problematičnih elemenata stvoriti izvorni tekst koji stroj lakše može prevesti. Pravila za pre-editing može čovjek primijeniti ručno ili automatski (Nitzke, 2019).…”

Section: Prededitiranje Posteditiranje I Kontrolirani Jezikunclassified

Pregled metoda obrade prirodnih jezika i strojnog prevođenja

Šuman

2021

Zb. Veleuč. Rij. (Online)

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U radu je dan pregled područja povezanog s procesiranjem prirodnih jezika i njihova međusobnog odnosa, počevši od šire domene kao što je umjetna inteligencija, putem strojnog učenja, računalne lingvistike, metoda strojnog prevođenja te posebice onih zasnovanim na dubokom učenju. Opisane su karakteristike, primjene, faze i glavni problemi obrade prirodnih jezika s leksičke, sintaktičke, semantičke, govorne i pragmatičke perspektive. Opisane su faze prepoznavanja i analize prirodnog jezika kao i faza generiranja prirodnih jezika. Postupci pre-editinga i post-editinga uz korištenje kontroliranih prirodnih jezika dani su kao primjeri prakse kojom se povećava točnost i kvaliteta automatskog prevođenja i općenito procesiranja teksta. Poseban je fokus stavljen na strojno prevođenje te metode strojnog prevođenja. Pristupi strojnom prevođenju kao statistički, temeljen na pravilima, hibridni i pristup temeljen na dubokom učenju opisani su i predstavljeni s obzirom na njihove prednosti i nedostatke i prikladnu primjenu u praksi. Na kraju su dani još uvijek neriješeni izazovi kao smjer daljnjih istraživanja vezanih uz obradu prirodnih jezika te značaj razvoja pristupa temeljenog na dubokom učenju.

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An Approach for Identifying Problem-Solving Activities in Post-Editing and Translation From Scratch

Cited by 13 publications

References 1 publication

Exploring undergraduate students’ experiences in dealing with post-editing of machine translation

Exploring undergraduate students’ experiences in dealing with post-editing of machine translation

Product and Process Analysis of Machine Translation into the Inflectional Language

Pregled metoda obrade prirodnih jezika i strojnog prevođenja

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