Showing papers on "Computer-assisted translation published in 2020"

Computer-Assisted Translation Tools: An Evaluation of Their Usability among Arab Translators

Abstract: Technology has become an essential part of the translation profession. Nowadays, computer-assisted translation (CAT) tools are extensively used by translators to enhance their productivity while maintaining high-quality translation services. CAT tools have gained popularity given that they provide a useful environment to facilitate and manage translation projects. Yet, little research has been conducted to investigate the usability of these tools, especially among Arab translators. In this study, we evaluate the usability of CAT tool from the translators’ perspective. The software usability measurement inventory (SUMI) survey is used to evaluate the system based on its efficiency, affect, usefulness, control, and learnability attributes. In total, 42 participants completed the online survey. Results indicated that the global usability of these tools is above the average. Results for all usability subscales were also above average wherein the highest scores were obtained for affect and efficiency, and the lowest scores were attributed to helpfulness and learnability. The findings suggest that CAT tool developers need to work further on the enhancement of the tool’s helpfulness and learnability to improve the translator’s experience and satisfaction levels. Further improvements are still required to increase the Arabic language support to meet the needs of Arab translators.

The Attitudes of Professional Translators and Translation Students towards Computer-Assisted Translation Tools in Yemen.

Abstract: The translation industry has witnessed rapid technological improvements in recent years This rapid improvement is ascribed to a huge demand for the workload Using a computer in the field of translation is very important due to the huge demand for fast and accurate translation Translation tools came to existence due to the low proficiency of machine translation CAT tools have become essential for many institutions, companies, and organizations CAT tools increase productivity and minimize translation costs In this study, the authors adopted Moore and Benbasat (1991) and Mahfouz (2018) instruments The questionnaire of this study composed of 27 statements distributed to four constructs- benefit of CAT tools, compatibility of CAT tools, ease of use of CAT tools, and image of the users of CAT tools The main purpose of this study is to investigate the attitudes of professional translators and translation students towards CAT tools in Yemen The analysis shows they show positive attitudes towards CAT tools The result of the study shows that professional translators and translation students show a positive attitude Unexpectedly, the profiles of the participants do not play any role in their attitudes towards CAT tools

The online computer-assisted translation classroom

Abstract: In the modern translation industry, all actors involved in the translation process communicate and collaborate increasingly – and oftentimes entirely – online using modern computer-assisted translation and project management software solutions. New translation technology needs new approaches to translator education and the Online Computer-Assisted Translation Classroom was designed to address this gap. Students are taught how to use the latest translation technology through hands-on remote software use and collaborative translation exercises. This article looks at the pedagogy of online translation teaching. It specifically discusses the teaching of translation technology and terminology management, drawing on process-oriented approaches to translator training and the method of cooperative translation.

Beyond the margins of academic education: identifying translation industry training practices through action research

Abstract: Digital technologies in the translation profession have given rise to the use of automated Computer Assisted Translation (CAT) tools and Machine Translation (MT), and Translation Service Providers are embracing these innovations as part of their workflows. Higher Education Institutions are also transforming their curricula to adapt to the changes brought about by technology (Austermuhl, 2006, 2013; Doherty, Kenny, & Way 2012; Doherty & Moorkens, 2013; Gaspari, Almaghout, & Doherty, 2015; Mellinger, 2017; Moorkens, 2017; O’Hagan, 2013; Rothwell & Svoboda, 2017). This research takes a phenomenological and ethnographical approach using action research as the methodology to see how the new digital skillsets are taught and used in the translation industry. As a trainer-researcher, I stay at translation companies to immerse myself in the training given to new employees. The results of this qualitative-type research derive from observations typically involving the trainer spending a full working week at the employers’ premises. The data set is hence collected based on workplace observations within the companies and on semi-structured interviews with translation company managers. This approach permits a very full understanding of the skills needed in the translation profession. What has been learned in the workplace can be applied at university in the training of future translators. Preliminary work suggests that MT and Artificial Intelligence (AI), while transforming the profession in many ways, are not yet overriding the need of sophisticated linguistic skills from trainee translators.

The Translator’s Extended Mind

Abstract: The rapid development of natural language processing in the last three decades has drastically changed the way professional translators do their work. Nowadays most of them use computer-assisted translation (CAT) or translation memory (TM) tools whose evolution has been overshadowed by the much more sensational development of machine translation (MT) systems, with which TM tools are sometimes confused. These two language technologies now interact in mutually enhancing ways, and their increasing role in human translation has become a subject of behavioral studies. Philosophers and linguists, however, have been slow in coming to grips with these important developments. The present paper seeks to fill in this lacuna. I focus on the semantic aspects of the highly distributed human–computer interaction in the CAT process which presents an interesting case of an extended cognitive system involving a human translator, a TM tool, an MT engine, and sometimes other human translators or editors. Considered as a whole, such a system is engaged in representing the linguistic meaning of the source document in the target language. But the roles played by its various components, natural as well as artificial, are far from trivial, and the division of linguistic labor between them throws new light on the familiar notions that were initially inspired by rather different phenomena in the philosophy of language, mind, and cognitive science.

Computer Assisted Translation with Neural Quality Estimation and Automatic Post-Editing

Abstract: With the advent of neural machine translation, there has been a marked shift towards leveraging and consuming the machine translation results. However, the gap between machine translation systems and human translators needs to be manually closed by post-editing. In this paper, we propose an end-to-end deep learning framework of the quality estimation and automatic post-editing of the machine translation output. Our goal is to provide error correction suggestions and to further relieve the burden of human translators through an interpretable model. To imitate the behavior of human translators, we design three efficient delegation modules -- quality estimation, generative post-editing, and atomic operation post-editing and construct a hierarchical model based on them. We examine this approach with the English--German dataset from WMT 2017 APE shared task and our experimental results can achieve the state-of-the-art performance. We also verify that the certified translators can significantly expedite their post-editing processing with our model in human evaluation.

Tenacious technophobes or nascent technophiles? A survey of the technological practices and needs of literary translators

Abstract: In a context of increasing investigation of technology use by translators of pragmatic texts, there appears to be an assumption that literary translation is a unique practice and that digital tools...

Computer Assisted Translation with Neural Quality Estimation and Automatic Post-Editing

Abstract: With the advent of neural machine translation, there has been a marked shift towards leveraging and consuming the machine translation results. However, the gap between machine translation systems and human translators needs to be manually closed by post-editing. In this paper, we propose an end-to-end deep learning framework of the quality estimation and automatic post-editing of the machine translation output. Our goal is to provide error correction suggestions and to further relieve the burden of human translators through an interpretable model. To imitate the behavior of human translators, we design three efficient delegation modules – quality estimation, generative post-editing, and atomic operation post-editing and construct a hierarchical model based on them. We examine this approach with the English–German dataset from WMT 2017 APE shared task and our experimental results can achieve the state-of-the-art performance. We also verify that the certified translators can significantly expedite their post-editing processing with our model in human evaluation.

Measuring Multimedia Content Proximity via Artificial Intelligence Methods

Abstract: The paper describes existing and novel approaches to word sequence similarity measuring which uses image processing procedures to reveal proximity relations between words and their meaning. This is implemented due to the fact the each word sequence can be associated with a particular pictorial domain, and thus any textual information can be potentially presented via an image series. Theoretical results of rule based approach, genetic algorithms and neural networks application are analyzed in terms of solving the problem under study. The proposed information processing technology may be useful for automatic translation applications, known as CAT-tools by now, search engine optimization, etc. The proposed content analysis techniques are designed to boost translation efficiency in particular. Romano-germanic and east-slavonic language pairs have been used as an example of practical application. It aids translation experts in finding the best solution for a specific domain that he (or she) is usually unfamiliar with. Thus, eliminating human errors and decreasing time needed for contextual search and deep examining of the topic.

Some Important Features of Two Computer-assisted Translation Tools: Wordfast and SDL Trados Studio

Abstract: In this paper, I will attempt to examine the features and functions of two tools in an analytical and comparative way. My focus will be on comparing and commenting on various features of their translation memory tools, such as matching functions, operational functions, alignment, etc. Through my experience with Wordfast and SDL Trados Studio, I found it very easy to use and to become familiar with SDL Trados. There are benefits and drawbacks to working with the TMs of both tools. In contrast to SDL Studio TM, Wordfast TM is very complicated to handle. In conjunction with my language pair, I found translating an HTML file with Wordfast complicated and time-consuming.

Application of Computer-Assisted Translation Technology in English Teaching

Abstract: Computer-assisted translation effectively combines English learning with professional learning, which can help students with certain English comprehensive ability to quickly translate and adapt to market needs, and provide new ideas for the special-purpose English teaching reform. It can be seen that it is necessary to study the establishment of English curriculum for computerassisted translation technology in colleges and universities. It can help students improve their translation efficiency in the professional field, improve their translation ability, and recognize more professional terminology to better meet the requirements of English for specialized purposes. Therefore, this study proposed a professional English translation teaching model based on computer-assisted translation technology for the current situation and existing problems of professional English translation teaching in colleges and universities. It also analysed and discusses from four aspects: teaching mode, teaching management function, curriculum setting and teaching method. The research results showed that the addition of computer-assisted translation technology to the classroom could have a positive impact on students' translation ability to a certain extent. Computer-assisted translation technology has practical significance for improving students' English application ability.