scholarly journals Machine translation systems and guidebooks: an approach to the importance of the role of the human translator

2020 ◽  
Author(s):  
Adrián Fuentes-Luque ◽  
Alexandra Santamaría Urbieta
Keyword(s):  
Machine Translation ◽  
Computer Assisted ◽  
Working Environments ◽  
Translation Tools ◽  
Technical Translation ◽  
Complete Translation ◽  
Translation Systems ◽  
Tourist Guides

Computer-assisted translation tools are increasingly supplemented by the presence of machine translation (MT) in different areas and working environments, from technical translation to translation in international organizations. MT is also present in the translation of tourism texts, from brochures to food menus, websites and tourist guides. Its need or suitability for use is the subject of growing debate. This article presents a comparative analysis of tourist guides translated by a human translator and three machine translation systems. The aims are to determine a first approach to the level of quality of machine translation in tourist texts and to establish whether some tourist texts can be translated using machine translation alone or whether human participation is necessary, either for the complete translation of the text or only for post-editing tasks.

scholarly journals Impact of computer-assisted translation tools by novice translators on the quality of written translations

2021 ◽  
Vol 7 (Extra-C) ◽  
pp. 714-721
Author(s):  
Zulfiya Akhatovna Usmanova ◽  
Ekaterina Nikolayevna Zudilova ◽  
Pavel Alekseevich Arkatov ◽  
Nataliaya Grigorievna Vitkovskaya ◽  
Ekaterina Vladimirovna Kravets
Keyword(s):  
Experimental Study ◽  
Literature Review ◽  
Machine Translation ◽  
Computer Assisted ◽  
Translation Tools ◽  
Translation Practice ◽  
Translation Systems ◽  
The Impact

The main specificity of the modern translation market is the translation of large volumes of technical texts and business documents in the shortest time possible. The purpose of the study is to conduct an experiment on the impact of machine translation systems (in terms of using term bases) on the efficiency of future translators. The study provides a literature review on the problem under study and presents the advantages of computer-assisted translation tools in translation practice. Based on the experimental study, the analysis of the influence of computer-assisted translation tools on the quality of written translations of student translators was carried out.

scholarly journals TURKISH TRANSLATION COMPANIES’ USE OF COMPUTER ASSISTED TRANSLATION TOOLS

2014 ◽  
Vol 2 ◽  
pp. 337-344
Author(s):  
Halil İbrahim Balkul ◽  
Hüseyin Ersoy
Keyword(s):  
Machine Translation ◽  
Information Technologies ◽  
The Body ◽  
Computer Assisted ◽  
Specific Time ◽  
Desktop Publishing ◽  
Work Demand ◽  
Translation Tools ◽  
Available Information ◽  
Translation Systems

Nowadays, Computer Assisted Translation (CAT) tools are undoubtedly among indispensable parts of both translation industry and academic translation world. Thanks to the variety of translation memories, machine translation systems, desktop publishing tools, and terminology management applications, the body of translations carried out in a specific time has increased in a considerable amount compared to the situation in past. In this regard, the current inquiry aims at investigating Turkish translation companies’ use of CAT tools via examining the websites of 39 translation companies, which are the members of two important national translation providers’ associations in Turkey.The results of the existing research are limited to the available information presented in the websites of the aforementioned translation companies about the use of CAT tools. Further studies can shed some light on the issue in a more overarching way if the number of translation companies to be examined is increased and questionnaires are delivered more accessibly, either by paper or online. Besides, this study is an attempt to emphasize that translation companies will have much more work demand from customers if they display information technologies they master on their websites.

scholarly journals Developing Statistical Machine Translation System for English and Nigerian Languages

2018 ◽  
pp. 1-8
Author(s):  
Ignatius Ikechukwu Ayogu ◽  
Adebayo Olusola Adetunmbi ◽  
Bolanle Adefowoke Ojokoh
Keyword(s):  
Error Analysis ◽  
Machine Translation ◽  
Statistical Machine Translation ◽  
Translation System ◽  
Parallel Corpora ◽  
Translation Tools ◽  
Global Demand ◽  
Machine Translation System ◽  
Translation Systems

The global demand for translation and translation tools currently surpasses the capacity of available solutions. Besides, there is no one-solution-fits-all, off-the-shelf solution for all languages. Thus, the need and urgency to increase the scale of research for the development of translation tools and devices continue to grow, especially for languages suffering under the pressure of globalisation. This paper discusses our experiments on translation systems between English and two Nigerian languages: Igbo and Yorùbá. The study is setup to build parallel corpora, train and experiment English-to-Igbo, (), English-to-Yorùbá, () and Igbo-to-Yorùbá, () phrase-based statistical machine translation systems. The systems were trained on parallel corpora that were created for each language pair using text from the religious domain in the course of this research. A BLEU score of 30.04, 29.01 and 18.72 respectively was recorded for the English-to-Igbo, English-to-Yorùbá and Igbo-to-Yorùbá MT systems. An error analysis of the systems’ outputs was conducted using a linguistically motivated MT error analysis approach and it showed that errors occurred mostly at the lexical, grammatical and semantic levels. While the study reveals the potentials of our corpora, it also shows that the size of the corpora is yet an issue that requires further attention. Thus an important target in the immediate future is to increase the quantity and quality of the data.  

scholarly journals The challenges of machine translation of academic publications

2021 ◽  
Author(s):  
D. A. Rew ◽  
N. G. Popova
Keyword(s):  
Machine Translation ◽  
Technology Development ◽  
Low Cost ◽  
Computer Assisted ◽  
Language And Culture ◽  
Arts And Humanities ◽  
Academic Publications ◽  
Training Programmes ◽  
Translation Systems

Clear translation remains a major challenge to better communication and understanding of the international academic literature, despite advances in Machine Translation (MT). Automatic translation systems which captured the detail and the sense of any manuscript in any language for a reader from any other linguistic background would find global applications.In this article, we discuss the current opportunities and constraints to the wider use of machine translation and computer-assisted human translation (CAT). At the present stage of technology development, these instruments offer a number of advantages to specialists working with scientific texts. These include the facility to skim and scan large amounts of information in foreign languages, and to act as digital dictionaries, thesauri and encyclopedias. Word-to-word and phrase-to-phrase translation between many languages and scripts is now well advanced.The availability of modern machine translation has therefore changed the work of specialist scientific translators, placing greater emphasis on more advanced text and sense editing skills. However, machine translation is still challenged by the nuances of language and culture from one society to another, particularly in the freestyle literature of the arts and humanities. Scientific papers are generally much more structured, but the quality of machine translation still largely depends on the quality of the source text. This varies considerably between different scientific disciplines and from one author to another.The most advanced translation systems are making steady progress. It is timely to revisit traditional training programmes in the field of written translation to focus on the development of higher-level research competencies, such as terminology search, and so to make best use of evolving machine translation technologies.More widely, we consider that there is a challenge across the higher education systems in all countries to develop a simple, clear and consistent “international” writing style to assist fast, reliable and low-cost machine translation and hence to advance mutual understanding across the global scientific literature.

scholarly journals Translation, from Pen-and-Paper to Computer-Assisted Tools (CAT Tools) and Machine Translation (MT)

Proceedings ◽  
2020 ◽  
Vol 63 (1) ◽  
pp. 56
Author(s):  
Bianca Han
Keyword(s):  
Machine Translation ◽  
Industry 4.0 ◽  
New Technology ◽  
Project Manager ◽  
Computer Assisted ◽  
Translation Process ◽  
Translation Tools

This paper reflects the technology-induced novelty of translation, which is perceived as a bridge between languages and cultures. We debate the extent to which the translation process maintains its specificity in the light of the new technology-enhanced working methods ensured by a large variety of Computer-Assisted Translation (CAT) and Machine Translation (MT) tools that aim to enhance the process, which includes the translation itself, the translator, the translation project manager, the linguist, the terminologist, the reviewer, and the client. This paper also hints at the topic from the perspective of the translation teacher, who needs to provide students with transversal competencies that are suitable for the digital area, supported by the ability to tackle Cloud-based translation tools, in view of Industry 4.0 requirements.

Development of a method for assessing the quality of machine translation based on ensemble methods in machine learning

2021 ◽  
Author(s):  
A.V. Kozina ◽  
Yu.S. Belov
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Quality Assessment ◽  
Machine Translation ◽  
Translation System ◽  
Human Judgment ◽  
Translation Quality ◽  
Machine Translation System ◽  
Translation Systems

Automatically assessing the quality of machine translation is an important yet challenging task for machine translation research. Translation quality assessment is understood as predicting translation quality without reference to the source text. Translation quality depends on the specific machine translation system and often requires post-editing. Manual editing is a long and expensive process. Since the need to quickly determine the quality of translation increases, its automation is required. In this paper, we propose a quality assessment method based on ensemble supervised machine learning methods. The bilingual corpus WMT 2019 for the EnglishRussian language pair was used as data. The text data volume is 17089 sentences, 85% of the data was used for training, and 15% for testing the model. Linguistic functions extracted from the text in the source and target languages were used as features for training the system, since it is these characteristics that can most accurately characterize the translation in terms of quality. The following tools were used for feature extraction: a free language modeling tool based on SRILM and a Stanford POS Tagger parts of speech tagger. Before training the system, the text was preprocessed. The model was trained using three regression methods: Bagging, Extra Tree, and Random Forest. The algorithms were implemented in the Python programming language using the Scikit learn library. The parameters of the random forest method have been optimized using a grid search. The performance of the model was assessed by the mean absolute error MAE and the root mean square error RMSE, as well as by the Pearsоn coefficient, which determines the correlation with human judgment. Testing was carried out using three machine translation systems: Google and Bing neural systems, Mouses statistical machine translation systems based on phrases and based on syntax. Based on the results of the work, the method of additional trees showed itself best. In addition, for all categories of indicators under consideration, the best results are achieved using the Google machine translation system. The developed method showed good results close to human judgment. The system can be used for further research in the task of assessing the quality of translation.

scholarly journals A Survey on Hybrid Machine Translation

2020 ◽  
Vol 184 ◽  
pp. 01061
Author(s):  
Anusha Anugu ◽  
Gajula Ramesh
Keyword(s):  
Machine Translation ◽  
Language Processing ◽  
Literature Survey ◽  
Neural Machine Translation ◽  
Translation Tools ◽  
Translation Techniques ◽  
Hybrid Machine ◽  
Hybrid Machine Translation ◽  
Translation Systems ◽  
Evaluation Techniques

Machine translation has gradually developed in past 1940’s.It has gained more and more attention because of effective and efficient nature. As it makes the translation automatically without the involvement of human efforts. The distinct models of machine translation along with “Neural Machine Translation (NMT)” is summarized in this paper. Researchers have previously done lots of work on Machine Translation techniques and their evaluation techniques. Thus, we want to demonstrate an analysis of the existing techniques for machine translation including Neural Machine translation, their differences and the translation tools associated with them. Now-a-days the combination of two Machine Translation systems has the full advantage of using features from both the systems which attracts in the domain of natural language processing. So, the paper also includes the literature survey of the Hybrid Machine Translation (HMT).

Function words in statistical machine-translated Chinese and original Chinese: A study into the translationese of machine translation systems

2018 ◽  
Vol 34 (4) ◽  
pp. 752-771
Author(s):  
Chen-li Kuo
Keyword(s):  
Machine Translation ◽  
Attribute Selection ◽  
Close Attention ◽  
Function Words ◽  
Rule Based ◽  
Source Language ◽  
Statistical Mt ◽  
Chinese Texts ◽  
Translation Systems

Abstract Statistical approaches have become the mainstream in machine translation (MT), for their potential in producing less rigid and more natural translations than rule-based approaches. However, on closer examination, the uses of function words between statistical machine-translated Chinese and the original Chinese are different, and such differences may be associated with translationese as discussed in translation studies. This article examines the distribution of Chinese function words in a comparable corpus consisting of MTs and the original Chinese texts extracted from Wikipedia. An attribute selection technique is used to investigate which types of function words are significant in discriminating between statistical machine-translated Chinese and the original texts. The results show that statistical MT overuses the most frequent function words, even when alternatives exist. To improve the quality of the end product, developers of MT should pay close attention to modelling Chinese conjunctions and adverbial function words. The results also suggest that machine-translated Chinese shares some characteristics with human-translated texts, including normalization and being influenced by the source language; however, machine-translated texts do not exhibit other characteristics of translationese such as explicitation.

scholarly journals Translator Education at a Crossroads:the Impact of Automation

2019 ◽  
Vol 64 (1) ◽  
pp. 103-121 ◽  
Author(s):  
Begoña Rodríguez de Céspedes
Keyword(s):  
Machine Translation ◽  
New Technologies ◽  
Service Providers ◽  
Computer Assisted ◽  
Daily Lives ◽  
Translation Tools ◽  
Technological Competence ◽  
The Future ◽  
The Impact ◽  
Translator Education

Abstract Automation is affecting all spheres of our daily lives and humans are adapting both to the challenges that it poses and the benefits that it brings. The translation profession has also experienced the impact of new technologies with Language Service Providers adapting to changes (Presas/Cid-Leal/Torres-Hostench 2016; Sakamoto/Rodríguez de Céspedes/Evans/Berthaud 2017). Translation trainers are not oblivious to this phenomenon. There have indeed been efforts to incorporate the teaching of digital translation tools and new technologies in the translation classroom (Doherty/Kenny/Way 2012; Doherty/Moorkens 2013; Austermühl 2013; O’Hagan 2013; Gaspari/Almaghout/Doherty 2015; Moorkens 2017) and many translation programmes in Europe are adapting their curricula to incorporate this necessary technological competence (Rothwell/Svoboda 2017). This paper reflects on the impact that automation and, more specifically machine translation and computer assisted tools, have and will have on the future training of translators and on the balance given by translation companies to language and technological skills.

scholarly journals A Review of Machine Translation Tools: The Translation’s Ability

2021 ◽  
Vol 16 (1) ◽  
pp. 162-176
Author(s):  
Tira Nur Fitria
Keyword(s):  
Machine Translation ◽  
Cognitive Abilities ◽  
Active Role ◽  
Translation Tools ◽  
The World ◽  
Human Skills ◽  
Translation Machine ◽  
One Machine ◽  
Descriptive Qualitative

The objective of the research is to review the ability of online machine translator tools includes Google Translate (GT), Collin Translator (CT), Bing Translator (BT), Yandex Translator (YT), Systran Translate (ST), and IBM Translator (IT). This research applies descriptive qualitative. The documentation was used in this study. The result of the analysis shows that the translation results are different, both from the style of language and the choice of words used by each machine translation tool. Thus, directly or indirectly, whether consciously or not, each translation machine carries its characteristics. Machine translation technology cannot be separated from the active role of humans. In other words, it will always be the best choice for users to rely on expert translation rather than machine translation. But no machine translator can be as accurate as human skills in producing translation products. In particular, the field of translation is also concerned with machine translation to support the performance of translators in analyzing the diction used as an element of language. In this regard, it needs to be underlined that the existence of machine translation is an additional facility in the world of translation, not as the main means of translation because the sophistication of the machine will not be able to match the flexibility of the human brain's cognitive abilities in adjusting the translation results according to the existing context. Accurate translation is sometimes subjective, relatively often temporal. Therefore, it is permissible for translating by more than one machine translator 

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