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Is Machine Translation Post-Editing Worth the Effort? a Survey of Research Into Post-Editing and Effort Maarit Koponen, University of Helsinki
The Journal of Specialised Translation Issue 25 – January 2016 Is machine translation post-editing worth the effort? A survey of research into post-editing and effort Maarit Koponen, University of Helsinki ABSTRACT Advances in the field of machine translation have recently generated new interest in the use of this technology in various scenarios. This development raises questions over the roles of humans and machines as machine translation appears to be moving from the peripheries of the translation field closer to the centre. The situation which influences the work of professional translators most involves post-editing machine translation, i.e. the use of machine translations as raw versions to be edited by translators. Such practice is increasingly commonplace for many language pairs and domains and is likely to form an even larger part of the work of translators in the future. While recent studies indicate that post-editing high-quality machine translations can indeed increase productivity in terms of translation speed, editing poor machine translations can be an unproductive task. The question of effort involved in post-editing therefore remains a central issue. The objective of this article is to present an overview of the use of post-editing of machine translation as an increasingly central practice in the translation field. Based on a literature review, the article presents a view of current knowledge concerning post-editing productivity and effort. Findings related to specific source text features, as well as machine translation errors that appear to be connected with increased post-editing effort, are also discussed. KEYWORDS Machine translation, MT quality, MT post-editing, post-editing effort, productivity. -
Translating the Post-Editor: an Investigation of Post-Editing Changes and Correlations with Professional Experience Across Two Romance Languages
Translating the post-editor: an investigation of post-editing changes and correlations with professional experience across two Romance languages Giselle de Almeida Thesis submitted for the degree of Doctor of Philosophy School of Applied Language and Intercultural Studies Dublin City University January 2013 Supervisors: Dr Sharon O’Brien and Phil Ritchie I hereby certify that this material, which I now submit for assessment on the programme of study leading to the award of Doctor of Philosophy is entirely my own work, that I have exercised reasonable care to ensure that the work is original, and does not to the best of my knowledge breach any law of copyright, and has not been taken from the work of others save and to the extent that such work has been cited and acknowledged within the text of my work. Signed: ______________________ ID No.: ______________________ Date: ______________________ ii Abstract With the growing use of machine translation, more and more companies are also using post-editing services to make the machine-translated output correct, precise and fully understandable. Post-editing, which is distinct from translation and revision, is still a new activity for many translators. The lack of training, clear and consistent guidelines and international standards may cause difficulties in the transition from translation to post- editing. Aiming to gain a better understanding of these difficulties, this study investigates the impact of translation experience on post-editing performance, as well as differences and similarities in post-editing behaviours and trends between two languages of the same family (French and Brazilian Portuguese). The research data were gathered by means of individual sessions in which participants remotely connected to a computer and post-edited machine-translated segments from the IT domain, while all their edits and onscreen activities were recorded via screen-recording and keylogging programs. -
INTRINSIC and EXTRINSIC SOURCES of TRANSLATOR SATISFACTION: an EMPIRICAL STUDY Mónica Rodríguez-Castro University of North Carolina at Charlotte (Estados Unidos)
Entreculturas 7-8 (enero 2016) ISSN: 1989-5097 Mónica Rodríguez Castro INTRINSIC AND EXTRINSIC SOURCES OF TRANSLATOR SATISFACTION: AN EMPIRICAL STUDY Mónica Rodríguez-Castro University of North Carolina at Charlotte (Estados Unidos) ABSTRACT This paper discusses the main results from an online questionnaire on translator satisfaction—a theoretical construct that conceptualizes leading sources of task and job satisfaction in the language industry. The proposed construct distinguishes between intrinsic and extrinsic sources of satisfaction using Herzberg’s two-factor framework and enumerates the constituents of translator satisfaction. Statistical analysis allows this study to quantify these constituents and their correlations. Preliminary results reveal that crucial sources of task satisfaction include task pride, ability to perform a variety of tasks, and successful project completion. Major sources of job satisfaction include professional skills of team members, a continuous relationship with clients, and clients’ understanding of the translation process. Low income and requests for discounts are found to be some of the sources of dissatisfaction. The findings from this study can be used to investigate new approaches for retention and human resource management. KEY WORDS: translation, language industry, task satisfaction, job satisfaction, outsourcing, sociology of translation. RESUMEN Este artículo presenta los principales resultados de una encuesta en línea que se enfoca en la satisfacción laboral del traductor en la actual industria de la lengua. La conceptualización teórica de la satisfacción laboral se divide en dos categorías fundamentales: satisfacción por tareas y satisfacción en el trabajo. El marco teórico establece una distinción entre fuentes intrínsecas y extrínsecas de satisfacción laboral adoptando como base los principios de la Teoría Bifactorial de Herzberg y enumera cada uno de los componentes de la satisfacción del traductor. -
Machine Translation Post-Editing and Effort, Empirical Studies on the Post-Editing Process
CORE Metadata, citation and similar papers at core.ac.uk Provided by Helsingin yliopiston digitaalinen arkisto Department of Modern Languages Faculty of Arts University of Helsinki Machine Translation Post-editing and Effort Empirical Studies on the Post-editing Process Maarit Koponen ACADEMIC DISSERTATION to be publicly discussed, by due permission of the Faculty of Arts at the University of Helsinki, in Auditorium XII, Main Building, on the 19th of March, 2016 at 10 o'clock. Helsinki 2016 Supervisor Prof. Lauri Carlson, University of Helsinki, Finland Pre-examiners Dr. Sharon O'Brien, Dublin City University, Ireland Dr. Jukka M¨akisalo,University of Eastern Finland, Finland Opponent Dr. Sharon O'Brien, Dublin City University, Ireland Copyright c 2016 Maarit Koponen ISBN 978-951-51-1974-2 (paperback) ISBN 978-951-51-1975-9 (PDF) Unigrafia Helsinki 2016 Abstract This dissertation investigates the practice of machine translation post-editing and the various aspects of effort involved in post-editing work. Through analy- ses of edits made by post-editors, the work described here examines three main questions: 1) what types of machine translation errors or source text features cause particular effort in post-editing, 2) what types of errors can or cannot be corrected without the help of the source text, and 3) how different indicators of effort vary between different post-editors. The dissertation consists of six previously published articles, and an introduc- tory summary. Five of the articles report original research, and involve analyses of post-editing data to examine questions related to post-editing effort as well as differences between post-editors. -
Context in Neural Machine Translation: a Review of Models and Evaluations
Context in Neural Machine Translation: A Review of Models and Evaluations Andrei Popescu-Belis University of Applied Sciences of Western Switzerland (HES–SO) School of Management and Engineering Vaud (HEIG–VD) Route de Cheseaux 1, CP 521 1401 Yverdon-les-Bains, Switzerland [email protected] January 29, 2019 Abstract features when translating entire texts, especially when this is vital for correct translation. Taking textual con- This review paper discusses how context has been text into account1 means modeling long-range depen- used in neural machine translation (NMT) in the dencies between words, phrases, or sentences, which past two years (2017–2018). Starting with a brief are typically studied by linguistics under the topics of retrospect on the rapid evolution of NMT models, discourse and pragmatics. When it comes to transla- the paper then reviews studies that evaluate NMT tion, the capacity to model context may improve certain output from various perspectives, with emphasis on those analyzing limitations of the translation of translation decisions, e.g. by favoring a better lexical contextual phenomena. In a subsequent version, choice thanks to document-level topical information, the paper will then present the main methods that or by constraining pronoun choice thanks to knowledge were proposed to leverage context for improving about antecedents. translation quality, and distinguishes methods that This review paper puts into perspective the signif- aim to improve the translation of specific phenom- icant amount of studies devoted in 2017 and 2018 to ena from those that consider a wider unstructured improve the use of context in NMT and measure these context. -
Final Study Report on CEF Automated Translation Value Proposition in the Context of the European LT Market/Ecosystem
Final study report on CEF Automated Translation value proposition in the context of the European LT market/ecosystem FINAL REPORT A study prepared for the European Commission DG Communications Networks, Content & Technology by: Digital Single Market CEF AT value proposition in the context of the European LT market/ecosystem Final Study Report This study was carried out for the European Commission by Luc MEERTENS 2 Khalid CHOUKRI Stefania AGUZZI Andrejs VASILJEVS Internal identification Contract number: 2017/S 108-216374 SMART number: 2016/0103 DISCLAIMER By the European Commission, Directorate-General of Communications Networks, Content & Technology. The information and views set out in this publication are those of the author(s) and do not necessarily reflect the official opinion of the Commission. The Commission does not guarantee the accuracy of the data included in this study. Neither the Commission nor any person acting on the Commission’s behalf may be held responsible for the use which may be made of the information contained therein. ISBN 978-92-76-00783-8 doi: 10.2759/142151 © European Union, 2019. All rights reserved. Certain parts are licensed under conditions to the EU. Reproduction is authorised provided the source is acknowledged. 2 CEF AT value proposition in the context of the European LT market/ecosystem Final Study Report CONTENTS Table of figures ................................................................................................................................................ 7 List of tables .................................................................................................................................................. -
Machine Translation and Monolingual Postediting: the AFRL WMT-14 System Lane O.B
Machine Translation and Monolingual Postediting: The AFRL WMT-14 System Lane O.B. Schwartz Timothy Anderson Air Force Research Laboratory Air Force Research Laboratory [email protected] [email protected] Jeremy Gwinnup Katherine M. Young SRA International† N-Space Analysis LLC† [email protected] [email protected] Abstract test set for correctness against the reference translations. Using bilingual judges, we fur- This paper describes the AFRL sta- ther evaluate a substantial subset of the post- tistical MT system and the improve- edited test set using a more fine-grained ade- ments that were developed during the quacy metric; using this metric, we show that WMT14 evaluation campaign. As part monolingual posteditors can successfully pro- of these efforts we experimented with duce postedited translations that convey all or a number of extensions to the stan- most of the meaning of the original source sen- dard phrase-based model that improve tence in up to 87.8% of sentences. performance on Russian to English and Hindi to English translation tasks. 2 System Description In addition, we describe our efforts We submitted systems for the Russian-to- to make use of monolingual English English and Hindi-to-English MT shared speakers to correct the output of ma- tasks. In all submitted systems, we use the chine translation, and present the re- phrase-based moses decoder (Koehn et al., sults of monolingual postediting of the 2007). We used only the constrained data sup- entire 3003 sentences of the WMT14 plied by the evaluation for each language pair Russian-English test set. -
WPTP 2015: Post-Editing Technology and Practice
Machine Translation Summit XV http://www.amtaweb.org/mt-summit-xv WPTP 2015: Post-editing Technology and Practice Organizers: Sharon O’Brien (Dublin City University) Michel Simard (National Research Council Canada) Joss Moorkens (Dublin City University) WORKSHOP MT Summit XV October 30 – November 3, 2015 -- Miami, FL, USA Proceedings of 4th Workshop on Post-Editing Technology and Practice (WPTP4) Sharon O'Brien & Michel Simard, Eds. Association for Machine Translation in the Americas http://www.amtaweb.org ©2015 The Authors. These articles are licensed under a Creative Commons 3.0 license, no derivative works, attribution, CC-BY-ND. Introduction The fourth Workshop on Post-Editing Technology and Practice (WPTP4) was organised for November 3rd, 2015, in Miami, USA, as a workshop of the XVth MT Summit. This was the fourth in a series of workshops organised since 2012 (WPTP1 – San Diego 2012, WPTP2 – Nice 2013, WPTP3 – Vancouver 2014). The accepted papers for WPTP4 cover a range of topics such as the teaching of post- editing skills, measuring the cognitive effort of post-editing, and quality assessment of post-edited output. The papers were also book-ended by two invited talks by Elliott Macklovitch (Independent Consultant) and John Tinsley (Iconic Translation Machines). Elliott Macklovitch’s talk was entitled “What Translators Need to Become Happy Post- Editors” while John Tinsley’s talk was entitled “What MT Developers Are Doing to Make Post-Editors Happy”. By juxtaposing these two points of view we hoped to provide an interesting frame for attendees where the views of users and developers were represented. We sincerely thank the authors of the papers as well as our two invited speakers for sharing their research. -
What Do Professional Translators Think About Post-Editing? Ana Guerberof Arenas, Universitat Rovira I Virgili, Tarragona
The Journal of Specialised Translation Issue 19 – January 2013 What do professional translators think about post-editing? Ana Guerberof Arenas, Universitat Rovira i Virgili, Tarragona ABSTRACT As part of a larger research project on productivity and quality in the post-editing of machine-translated and translation-memory outputs, 24 translators and three reviewers were asked to complete an on-line questionnaire to gather information about their professional experience but also to obtain data on their opinions about post-editing and machine translation. The participants were also debriefed after finalising the assignment to triangulate the data with the quantitative results and the questionnaire. The results show that translators have mixed experiences and feelings towards machine-translated output and post-editing, not necessarily because they are misinformed or reluctant to accept its inclusion in the localisation process but due to their previous experience with various degrees of output quality and to the characteristics of this type of projects. The translators were quite satisfied in general with the work they do as translators, but not necessarily with the payment they receive for the work done, although this was highly dependent on different customers and type of tasks. KEYWORDS Translation memory, machine translation, post-editing, review, professional translators, reviewers, experience, localisation, output, pricing, MT, TM. 1. Introduction It is not very often that translators are asked their opinions about post- editing and machine translation in the localisation industry. This could be out of fear of an adverse or negative response or due to the fact that translators are often invisible in the localisation work-flow, and we feel this invisibility is increasing as process automation increases, and all aspects related to technology seem to acquire more relevance than the act of translating itself. -
A Comparison of Free Online Machine Language Translators Mahesh Vanjani1,* and Milam Aiken2 1Jesse H
Journal of Management Science and Business Intelligence, 2020, 5–1 July. 2020, pages 26-31 doi: 10.5281/zenodo.3961085 http://www.ibii-us.org/Journals/JMSBI/ ISBN 2472-9264 (Online), 2472-9256 (Print) A Comparison of Free Online Machine Language Translators Mahesh Vanjani1,* and Milam Aiken2 1Jesse H. Jones School of Business, Texas Southern University, 3100 Cleburne Street, Houston, TX 77004 2School of Business Administration, University of Mississippi, University, MS 38677 *Email: [email protected] Received on 5/15/2020; revised on 7/25/2020; published on 7/26/2020 Abstract Automatic Language Translators also referred to as machine translation software automate the process of language translation without the intervention of humans While several automated language translators are available online at no cost there are large variations in their capabilities. This article reviews prior tests of some of these systems, and, provides a new and current comprehensive evaluation of the following eight: Google Translate, Bing Translator, Systran, PROMT, Babylon, WorldLingo, Yandex, and Reverso. This re- search could be helpful for users attempting to explore and decide which automated language translator best suits their needs. Keywords: Automated Language Translator, Multilingual, Communication, Machine Translation published results of prior tests and experiments we present a new and cur- 1 Introduction rent comprehensive evaluation of the following eight electronic automatic language translators: Google Translate, Bing Translator, Systran, Automatic Language Translators also referred to as machine translation PROMT, Babylon, WorldLingo, Yandex, and Reverso. This research software automate the process of language translation without the inter- could be helpful for users attempting to explore and decide which auto- vention of humans. -
Machine Translation in the Field of Law: a Study of the Translation of Italian Legal Texts Into German
Comparative Legilinguistics vol. 37/2019 DOI: http://dx.doi.org/10.14746/cl.2019.37.4 MACHINE TRANSLATION IN THE FIELD OF LAW: A STUDY OF THE TRANSLATION OF ITALIAN LEGAL TEXTS INTO GERMAN EVA WIESMANN, Prof., PhD Department of Interpreting and Translation, University of Bologna Corso della Repubblica 136, 47121 Forlì, Italy [email protected] ORCID: https://orcid.org/0000-0001-9414-8038 Abstract: With the advent of the neural paradigm, machine translation has made another leap in quality. As a result, its use by trainee translators has increased considerably, which cannot be disregarded in translation pedagogy. However, since legal texts have features that pose major challenges to machine translation, the question arises as to what extent machine translation is now capable of translating legal texts or at least certain types of legal text into another legal language well enough so that the post- editing effort is limited, and, consequently, whether a targeted use in translation pedagogy can be considered. In order to answer this question, DeepL Translator, a machine translation system, and MateCat, a CAT system that integrates machine translation, were tested. The test, undertaken at different times and without specific translation memories, provided Eva Wiesmann: Machine Translation in… for the translation of several legal texts of different types utilising both systems, and was followed by systematisation of errors and evaluation of translation results. The evaluation was carried out according to the following criteria: 1) comprehensibility and meaningfulness of the target text; and 2) correspondence between source and target text in consideration of the specific translation situation. -
Investigating Usability in Postediting Neural Machine Translation: Evidence from Translation Trainees' Self-Perception And
Across Languages and Cultures 22 (2021) 1, 100–123 DOI: 10.1556/084.2021.00006 Investigating usability in postediting neural machine translation: Evidence from translation trainees’ self-perception and performance Xiangling Wang1p , Tingting Wang1, Ricardo Munoz~ Martın2 and Yanfang Jia3 1 School of Foreign Languages, Hunan University, Changsha, China 2 MC2 Lab, University of Bologna, Bologna, Italy 3 Research Institute of Languages and Cultures, Hunan Normal University, Changsha, China ORIGINAL RESEARCH PAPER Received: January 6, 2020 • Accepted: October 5, 2020 © 2021 Akademiai Kiado, Budapest ABSTRACT This is a report on an empirical study on the usability for translation trainees of neural machine translation systems when post-editing (MTPE). Sixty Chinese translation trainees completed a questionnaire on their perceptions of MTPE’s usability. Fifty of them later performed both a post-editing task and a regular translation task, designed to examine MTPE’s usability by comparing their performance in terms of text processing speed, effort, and translation quality. Contrasting data collected by the questionnaire, key- logging, eyetracking and retrospective reports we found that, compared with regular, unaided translation, MTPE’s usefulness in performance was remarkable: (1) it increased translation trainees’ text processing speed and also improved their translation quality; (2) MTPE’s ease of use in performance was partly proved in that it significantly reduced informants’ effort as measured by (a) fixation duration and fixation counts; (b) total task time; and (c) the number of insertion keystrokes and total keystrokes. However, (3) translation trainees generally perceived MTPE to be useful to increase productivity, but they were skeptical about its use to improve quality.