Quality expectations of machine translation

Machine Translation (MT) is being deployed for a range of use-cases by millions of people on a daily basis. There should, therefore, be no doubt as to the utility of MT. However, not everyone is convinced that MT can be useful, especially as a productivity enhancer for human translators. In this chapter, I address this issue, describing how MT is currently deployed, how its output is evaluated and how this could be enhanced, especially as MT quality itself improves. Central to these issues is the acceptance that there is no longer a single ‘gold standard’ measure of quality, such that the situation in which MT is deployed needs to be borne in mind, especially with respect to the expected ‘shelf-life’ of the translation itself

Quality Evaluation of C-E Translation of Legal Texts by Mainstream Machine Translation Systems—An Example of DeepL and Metasota

Despite significant progress made in machine translation technology and the ongoing efforts in practical and commercial application of neural machine translation systems, their performance in vertical fields remains unsatisfactory. To avoid misunderstandings and excessive expectations of a specific machine translation system, this research selected legal texts as its real data research object. The text translation tasks were accomplished using two popular neural machine translation systems, DeepL and Metasota, both domestically and internationally, and evaluated using internationally recognized BLEU algorithm to reflect their Chinese-to-English translation performance in legal fields. Based on the determined BLEU score, the study adopted an artificial analysis method to analyze the grammatical aspects of the machine translation output, including the accuracy of terminology usage, word order, subject-verb agreement, sentence structure, tense, and voice to enable readers to have a rational understanding of the gap between machine translation and human translation in legal text translation, and objectively assess the application and future development prospects of machine translation in legal text fields. The experimental results indicate that machine translation systems still face challenges in achieving high-quality legal text translations and meeting practical needs, and that further post-translation editing research is needed to improve the accuracy of legal text translation

L'intégration de la révision et de la post-édition dans la formation en traduction

Since the first studies observing pedagogical activities related to quality in translator training, many evolutions have taken place, in training programmes as well as in the professional world. Revision has gained a more streamline position in translation processes, and post-editing more and more visible, aided by the improvement of Neural Machine Translation (NMT) quality. These two activities, which aim at upgrading human translations, for revision, and machine translations, for post-editing, still respond to different expectations, practices and document types. However, the role of the skilled expert is acknowledged in normative texts about both activities, and the sealed barriers that existed before between human translation, assisted translation and machine translation, are increasingly blurred. In this paper, we will endeavour to set an integrated and balanced positioning of post-editing in translation training, leveraging the strengths and weaknesses of human translation as much as machine translation, in order to contribute to the long-lasting value of the professional translation specialist

Il settore della traduzione oggi

The use of Machine Translation (MT) and Neural Machine Translation (NMT) in professional translation activities is not only changing how translators work, but also altering how projects are managed and the expectations they entail within translation supply chains. The challenges posed by MT and NMT imply an increasingly involved role for translators in both company strategies and the managerial aspects of translation. This contribution aims to present the new professional opportunities and challenges in the translation industry considering the evolution of artificial intelligence, which has made automatic translation more precise and efficient, but has also raised concerns about the employability of human translators. Given the heightened complexity due to technological development and globalization, there might be a need for increased industry regulation, involving the establishment of new certification programs and the adoption of best practices to ensure the high quality of produced translations

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

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

Teaching machine translation and translation technology: a contrastive study

The Machine Translation course at Dublin City University is taught to undergraduate students in Applied Computational Linguistics, while Computer-Assisted Translation is taught on two translator-training programmes, one undergraduate and one postgraduate. Given the differing backgrounds of these sets of students, the course material, methods of teaching and assessment all differ. We report here on our experiences of teaching these courses over a number of years, which we hope will be of interest to lecturers of similar existing courses, as well as providing a reference point for others who may be considering the introduction of such material

Translation and human-computer interaction

This paper seeks to characterise translation as a form of human-computer interaction. The evolution of translator-computer interaction is explored and the challenges and benefits are enunciated. The concept of cognitive ergonomics is drawn on to argue for a more caring and inclusive approach towards the translator by developers of translation technology. A case is also made for wider acceptance by the translation community of the benefits of the technology at their disposal and for more humanistic research on the impact of technology on the translator, the translation profession and the translation process