Translators and machine translation: knowledge and skills gaps in translator pedagogy

Mellinger, Christopher D.

doi:10.1080/1750399x.2017.1359760

Cited by 80 publications

(53 citation statements)

References 21 publications

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“…The analysis of the interviews also has implications for how translators are trained. There has been much emphasis lately on how MT should be integrated into translation curricula and how post-editing and MT engine development skills should have more weight in translation teaching (e.g., Mellinger, 2017;Plaza Lara, 2019). A strong focus on MT is indeed a key component of preparing translators for practice.…”

Section: Resultsmentioning

confidence: 99%

Translating perceptions and managing expectations: an analysis of management and production perspectives on machine translation

Vieira

Jiménez

2019

Perspectives

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The use of machine translation (MT) in professional translation tasks can change not only how translators work, but also how projects are managed and the expectations they entail across translation supply chains. Previous research has looked extensively into translators' attitudes to MT but has often ignored important aspects of how translators' views interact with those of other language industry stakeholders. This article presents a contrastive analysis of attitudes to MT which covers management and production perspectives. The discussion draws on semi-structured interviews which were thematically coded and qualitatively examined. The study shows how MT adds uncertainty to translation production networks. It argues that the challenges posed by MT are exacerbated by how the current makeup of the language industry restricts translators' field of influence to texts while possibly alienating them from wider aspects of business strategy. The article makes two suggestions. First, it calls for increased translator involvement in the management aspects of service provision. Second, it emphasises the need for a deeper discussion of MT which, rather than framing the technology itself as a potential 'threat', addresses broader societal issues involving misguided perceptions and mismatched expectations. ARTICLE HISTORY

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Section: Resultsmentioning

confidence: 99%

Translating perceptions and managing expectations: an analysis of management and production perspectives on machine translation

Vieira

Jiménez

2019

Perspectives

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“…When the classical taskbased or project-based situated learning is adopted in the CAT classroom, students develop both instrumental and critical-thinking techniques through role adoption and the recreation of quasi-real translation activities or scenarios, previously designed by the teacher. While this is the most common form of situated learning, it is often argued that the simulation of a computer-assisted translation task or project should not take place in isolation but rather be embedded in practical translation courses (Pym 2013;Mellinger 2017).…”

Section: Pedagogic Approaches and Methodsmentioning

confidence: 99%

Translation and technology

O’Brien¹,

Vázquez²

2019

The Routledge Handbook of Translation and Education

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INTRODUCTIONTranslation Technology, Translation Tools, Translation Environment Tools (or TEnTs) andComputer-Aided Translation (or CAT) are frequently used as synonyms. In its broadest sense translation technology is understood to include a large array of computer tools that help translators do their jobs, including word processors, spell, style and grammar checkers, the World Wide Web, corpus compilation and analysis tools, terminology management tools, translation memory tools (TM), translation management systems (TMS) and machine translation (MT). Bowker (2002 p. 7) arranges these tools along a continuum from less automated (human translation) to more automated (machine translation), with CAT positioned in the middle. In the human translation rubric, she includes, for example, word processors and spell checkers, and in CAT, translation memory, corpus analysis tools, terminology management systems, data capture tools, localisation and web-page translation tools, and diagnostic tools. The MT rubric includes only machine translation systems. This extensive list is evidence of how technologised the translation profession is. For the sake of clarity throughout this chapter, we refer to translation technology broadly speaking as Computer-Aided Translation -CAT. Where machine translation is specifically meant, we use that term.Likewise, when we want to draw attention to a specific type of tool, we use the exact term, e.g. terminology management tool or translation memory (TM).Over the last decades, parts of the translation profession have moved from deploying hardly any technology (in the 1980s), to embracing of Translation Memory and Terminology Management (in the 1990s), to the introduction of MT and its convergence with TM tools.Industry commentators predict a move towards Fully-Automatic Useful Translation -or FAUT -by 2030 (Massardo and van der Meer 2017). Currently, translators are still expected to produce high quality translation and that is often done with the aid of CAT tools. For this reason, it is important that translation technology is firmly embedded in the translator training curriculum. As Bowker (2002) points out, knowledge of CAT increases employability of graduates, but there are additional benefits to the teaching of translation technology: students can become more attuned to their own and to peer approaches to translation, data is created for research into translation, and reflections on the impact of technology on process, product and profession can be generated (ibid).This chapter will first discuss early considerations on teaching translation technology. We select a subset of examples to give an overview of what these early considerations entailed. A number of formal translator competence models are examined so as to illustrate the place of translation technology in these models. Next, we provide a synopsis of research concerns relating to translation technology. Then, we review the pedagogical approaches adopted these days for CAT teaching before turning to conclusions, where we outline curre...

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“…Bu anlamda Guerberof (2008) çeviride düzeltmeyi öğreten bir kursun geliştirilebileceğini, bu kursta postediting bağlamında farklı makine çevirisi teknolojilerine ilişkin arka plan bilgisinin verilebileceğini ve öğrencilere makine çevirisinden çıkan ham metni düzeltmede uygulamalı ödevlerin yararlı olacağını vurgulamıştır. Bu konuda Mellinger (2017) ise müfredatların düzenlenmesine ilişkin yaklaşımların, çeviri piyasasının gereksinimleriyle uyum içerisinde olması gerektiğini, böylece öğrencilerin mezuniyet sonrası piyasada doğru yerlerde konumlanabileceğini yinelemiştir.…”

Section: Makine çEvirisinin çEviribilim Ve Akademik çEviri Eğitimi Açunclassified

Makine çevirisi sonrası düzeltme işlemine (post-editing) yönelik kapsamlı bir inceleme

Çetiner

2019

RumeliDE Dil Ve Edebiyat Araştırmaları Dergisi

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Makine Çevirisine yönelik son yıllarda artan bir talep görülmektedir. Diğer bir ifadeyle makine çevirisi sistemlerindeki güncel gelişmeler hem çeviri piyasasında hem de çeviriye ilişkin akademik çevrelerde ilgi uyandırmıştır. Böylece, bir zamanlar ALPAC raporuyla kesintiye uğrayan "Tam Otomatik Yüksek Kalitede Makine Çevirisine" yönelik umutlar tekrar canlanmıştır. Ancak farklı birçok deneysel çalışmada ortaya konduğu üzere makine çevirisi sistemleri henüz, herhangi bir düzeltme gerektirmeden kolayca yayımlanabilir çeviri ürünleri ortaya koyacak durumda değildir. Bu şartlar altında "Makine Çevirisi Sonrası Düzeltme İşlemi" (Post-Editing) isimli yeni bir araştırma alanı ortaya çıkmıştır. Literatürdeki en yaygın tanıma göre post-editing, makine çevirisi tarafından çevrilen bir metnin düzeltilmesi veya değiştirilmesi anlamına gelmektedir. Bu tanım normal bir çevirmen ile Makine Çevirisi Sonrası Düzeltme İşlemini (post-editing) gerçekleştiren çevirmen arasındaki ayrıma dikkat çekmektedir. Ayrıca, ilgili alanyazında belirtildiği üzere, nihai çeviri ürününün kalitesi büyük ölçüde makine çevirisinden çıkan ham çeviriye bağlıdır. Bu yüzden kontrollü dil kuralları veya ön-düzeltme adımları gibi parametreler makine çevirisinden çıkan ham çevirinin yüksek kalitede olmasını sağlayan etkenler olarak ön plana çıkmıştır. Ayrıca, çevirmenin rolü ve dahil olduğu süreç dikkate alındığında Makine Çevirisi Sonrası Düzeltme İşlemi, Çeviribilimde yeni paradigma değişimlerinin yolunu açmıştır. Ancak, tüm bu hususlar ve kavramlar ilgili alanyazında birbirinden bağımsız olarak açıklanmaktadır. Bu yüzden bu çalışma betimleyici bir metotla bu kavramları kapsamlı olarak ele almayı, birbirleriyle ilişkilendirmeyi ve Makine Çevirisi Sonrası Düzeltme İşleminin yerini Çeviribilimdeki dönemler açısından incelemeyi amaçlamaktadır.Anahtar kelimeler: Makine çevirisi, makine çevirisi sonrası düzeltme işlemi (post-editing), öndüzeltme işlemi, kontrollü dil kuralları.

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Translators and machine translation: knowledge and skills gaps in translator pedagogy

Cited by 80 publications

References 21 publications

Translating perceptions and managing expectations: an analysis of management and production perspectives on machine translation

Translating perceptions and managing expectations: an analysis of management and production perspectives on machine translation

Translation and technology

Makine çevirisi sonrası düzeltme işlemine (post-editing) yönelik kapsamlı bir inceleme

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