Postediting machine translation output and its revision: subject-matter experts versus professional translators

El presente estudio compara la post-edición de textos técnicos de ingenieros y traductores profesionales en términos de velocidad, documentación y cambios. También se compara la calidad de los textos post-editados. Además, se explora cuál de los siguientes flujos de trabajo es más rápido y produce resultados de mayor calidad: la post-edición de los resultados de Traducción Automática hecha por los ingenieros y la revisada por traductores profesionales, o viceversa. Los resultados sugieren que la experiencia y conocimientos en la materia son los principales factores que determinan la calidad de la post-edición. Cuando se penalizan los errores recurrentes, la post-edición de textos técnicos realizada por los ingenieros es significativamente de mayor calidad que la de los traductores. La velocidad de revisión de traductores e ingenieros no difirió significativamente. En textos técnicos, la mejora de la calidad que conlleva que el ingeniero revise la post-edición del traductor es mayor que en cuando el trabajo se organiza al revés. Además, la calidad de los textos post-editados y sus versiones revisadas (ya sea realizada por traductores profesionales o ingenieros) cambia significativamente según se penalicen o no los errores recurrentes.El present estudi compara la post-edició de textos tècnics d'enginyers i traductors professionals en termes de velocitat, documentació i canvis. També es compara la qualitat dels textos post-editats. A més, s'explora quin dels següents fluxos de treball és més ràpid i produeix resultats de major qualitat: la post-edició dels resultats de Traducció Automàtica feta pels enginyers i la revisada per traductors professionals, o viceversa. Els resultats suggereixen que l'experiència i coneixements en la matèria són els principals factors que determinen la qualitat de la post-edició. Quan es penalitzen els errors recurrents, la post-edició de textos tècnics realitzada pels enginyers és significativament de major qualitat que la dels traductors. La velocitat de revisió de traductors i enginyers no va diferir significativament. En textos tècnics, la millora de la qualitat que comporta que l'enginyer revisi la post-edició del traductor és major que en quan el treball s'organitza a l'inrevés. A més, la qualitat dels textos post-editats i les seves versions revisades (ja sigui realitzada per traductors professionals o enginyers) canvia significativament segons es penalitzin o no els errors recurrents.The present research compares engineers’ and professional translators’ postediting a technical text in terms of speed, documentation and changes. It also compares the postedited texts with regard to quality. Further, we explore which of the following workflows is faster and produces outputs of higher quality: Postediting MT output by engineers and revising the postedited text by professional translators, or vice-versa. The findings suggest that expertise and experience in the subject-matter are the main factors determining postediting quality. When the recurrent errors are penalized, the engineers’ postediting of technical texts is of significantly higher quality than the translators’. The translators’ and the engineers’ postediting and revision speed did not differ significantly. For technical texts, the quality improvement brought about by engineer-revision of translator-postediting is higher than vice-versa. Further, the quality of the postedited texts and their revised versions (either performed by professional translators or engineers) changes significantly as a result of penalizing and unpenalizing recurrent errors

Skills and Profile of the New Role of the Translator as MT Post-editor

This paper explores the skills and profile of the new role of the translator as MT post-editor in view of the rising interest and use of MT in the translation industry. After a brief review of the relevant literature declaring post-editing (PE) as a profession on its own, the paper goes on to identify the different tasks involved in PE processes, following the work of Krings (Krings, 2001). Then, a series of competences are defined and grouped into three main categories: core competences, linguistic skills and instrumental competences. Finally, a description of the controlled translation scenario of MT PE is advanced taking into account the overall scenario of any translation project, including client description, text domain, text description, use of glossaries, MT engine, MT output quality and purpose of the translated text.Aquest article aborda les habilitats i les característiques del perfil del nou rol del traductor com a posteditor de traducció automàtica, tot i tenint en compte l'augment de l'interès en i l'ús de la traducció automàtica per part de la industria de la traducció. Després d'una breu revisió de la literatura més rellevant sobre postedició (PE) en tant que professió per ella mateixa, l'article identifica les diferents tasques implicades en els processos de PE, segons la proposta de Krings (2001). A continuació es defineix una sèrie de competències que s'agrupen en tres categories principals: competències nuclears, habilitats lingüístiques i competències instrumentals. Finalment el artículo proposa una descripció de l'escenari de traducció controlada propi de la PE de traducció automàtica, sense perdre de vista l'escenari general de qualsevol projecte de traducció, que inclou la descripció del client, el domini del text, la descripció del text, l'ús de glossaris, el motor de traducció automàtica, la qualitat de la traducció automàtica resultant i el propòsit del text traduït.Este artículo aborda las habilidades y las características del perfil del nuevo rol del traductor como poseditor de traducción automática, a la luz del aumento del interés en y del uso de la traducción automática por parte de la industria de la traducción. Después de una breve revisión de la literatura más relevante sobre posedición (PE) en tanto que profesión por sí misma, en el artículo se identifican las diferentes tareas implicadas en los procesos de PE, según la propuesta de Krings (2001). A continuación se define una serie de competencias que se agrupan en tres categorías principales: competencias nucleares, habilidades lingüísticas y competencias instrumentales. Finalmente el artículo propone una descripción del escenario de traducción controlada propio de la PE de traducción automática, sin perder de vista el marco general de cualquier proyecto de traducción, que incluye la descripción del cliente, el dominio del texto, la descripción del texto, el uso de glosarios, el motor de traducción automática, la calidad de la traducción automática resultante y el propósito del texto traducido

Translators and machine translation : book of presentations

El Tradumàtica Research Group està format, entre d'altres, per: Olga Torres-Hostench, Adrià Martín-Mor, Pilar Cid-Leal, Ramon Piqué Huerta, Anna Aguilar-Amat, Marisa Presas, Pilar Sánchez-Gijón, Inna Kozlov

Multimedia for language learning

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 79-81).Students studying foreign languages often wish to enjoy authentic foreign-language content - for example, foreign-language videos and comics. Existing means of presenting this content, however, are suboptimal from the perspective of language learning. We have developed a pair of tools that aim to help learners acquire the foreign language while enjoying authentic, foreign-language material. One tool is Smart Subtitles, which help learners learn vocabulary while watching videos. Our user evaluations have shown that Smart Subtitles help learners learn vocabulary more effectively than a popular approach for learning from video (dual subtitles). The other tool is a grammar visualization which illustrates the grammatical structure of sentences. This grammar visualization can be embedded into a number of language-learning applications. This includes a foreign-language manga reader we have built, which aims to help learners learn vocabulary, grammar and pronunciation while reading comics and manga. Our study for the grammar visualization shows that it helps monolinguals arrive at more accurate translations if we have an oracle taking the best translation of all, though there was no significant improvement in the average translation quality.by Geza Kovacs.M. Eng

What Do Professional Translators Do when Post-Editing for the First Time? First Insight into the Spanish-Basque Language Pair

Machine translation post-editing is becoming commonplace and professional translators are often faced with this unknown task with little training and support. Given the different translation processes involved during post-editing, research suggests that untrained translators do not necessarily make good post-editors. Besides, the post-editing activity will be largely influenced by numerous aspects related to the technology and texts used. Training material, therefore, will need to be tailored to the particular conditions under which post-editing is bound to happen. In this work, we provide a first attempt to uncover what activity professional translators carry out when working from Spanish into Basque. Our initial analysis reveals that when working with moderate machine translation output post-editing shifts from the task of identifying and fixing errors, to that of “patchwork” where post-editors identify the machine translated elements to reuse and connect them using their own contributions. Data also reveal that they primarily focus on correcting machine translation errors but often fail to restrain themselves from editing correct structures. Both findings have clear implications for training and are a step forward in tailoring sessions specifically for language combinations of moderate quality

Systems Combination for Grammatical Error Correction

Master'sMASTER OF SCIENC

The Professional Profile of a Post-editor according to LSCs and Linguists: a Survey-Based Research

The boundaries between translation technologies are fading and language professionals are heading towards a pluri- and transdisciplinary job description, for which the use of CAT tools, translation management systems, and machine translation (MT) are compulsory. “Language paraprofessionals”, “paralinguists”, “language consultants”, “digital linguists”, and a long list of other titles is emerging to refer to the professionals who master a number of features of several tools, while remaining attentive to linguistics (see Bond 2018). According to TAUS DQF Dashboard data presented in TAUS Newsletter the 1st of May of 2019, the industry averages show that 9.7% of the translation output origin comes from MT and that 1,057 words per hour are post-edited on average. This has clear repercussions on the profession from the employability perspective.With 66 submissions by LSCs and industry stakeholders, and 142 answers from individuals (in-house or freelance translators), we present the most salient subject matters from and for the translation industry regarding MT post-editing. Some represent gaps to be filled; others represent common ground already found. Thanks to this up-to-date knowledge of the globalization landscape, clear goals can be set, and the way is paved for evolution.&nbsp

Syntax-Driven Machine Translation as a Model of ESL Revision

Abstract In this work, we model the writing revision process of English as a Second Language (ESL) students with syntax-driven machine translation methods. We compare two approaches: tree-to-string transformation

Post-editing of machine translation output with and without source text

Post-editing of machine translation output is a practice which aims to speed up translation production and distribution of information. There is still no consensus regarding the question of whether post-editors should have access to the source text of the translations they are post-editing. The aim of this paper was to see how access to source text influences post-editors’ quality of work and their speed, which is directly related to productivity. An experiment was conducted among 22 graduate students of English, who post-edited two translations about the European Union produced by Google Translate. The subjects were divided into two groups and each had access to the source text for only one of the translations. In the experiment, it was measured how long it took to post-edit the texts and how many errors in the MT output the subjects were able to correct. The errors were analyzed and divided into categories in order to get a more precise picture. Contrary to expectations, access to source text was found not to have significant impact on speed. As expected, it did have an impact on the quality of the final translation