Online Machine Translation Research Articles

Universals in machine translation?

Abstract By examining and comparing the linguistic patterns in a self-built corpus of Chinese-English translations produced by WeChat Translate, the latest online machine translation app from the most popular social media platform (WeChat) in China, this study explores such questions as whether or not and to what extent simplification and normalization (hypothesized Translation Universals) exhibit themselves in these translations. The results show that, whereas simplification cannot be substantiated, the tendency of normalization to occur in the WeChat translations can be confirmed. The research finds that these results are caused by the operating mechanism of machine translation (MT) systems. Certain salient words tend to prime WeChat’s MT system to repetitively resort to typical language patterns, which leads to a significant overuse of lexical chunks. It is hoped that the present study can shed new light on the development of MT systems and encourage more corpus-based product-oriented research on MT.

Attitudes to the use of Google Translate for L2 production: analysis of chatroom discussions among UK secondary school students

ABSTRACT This paper presents the findings of a research project on UK school students’ attitudes to the use of Free Online Machine Translation for L2 production and more specifically in preparing for assessment. Data were collected from a publicly available online forum to analyse students’ spontaneous discussion of the use of Free Online Machine Translation, predominantly Google Translate. The majority of relevant comments were posted by secondary school students in the UK, regarding the use of Google Translate for GCSE examinations. The findings reveal that use of Google Translate for assignments was accepted practice among secondary school students in the UK over the last decade. However, they show mixed attitudes to this usage, and the nature of the discussion changed over the decade as a result of the evolution of Google Translate and changes to UK examination requirements. This study is original in its use of netnography, the study of online communities, to analyse students’ comments to each other about their use of Google Translate in preparing for modern foreign languages (MFL) coursework. These findings, therefore, serve to inform the debate on how schools and universities should respond to student Google Translate usage for language learning and assignments.

Machine Translation in the Language Classroom: Turkish EFL Learners’ and Instructors’ Perceptions and Use

Online machine translation (OMT) tools are not exclusively designed for language learners; however, these tools are popular among them. This quantitative study investigated the perceptions and attitudes of Turkish speaking EFL learners and instructors in a university English program regarding the use of OMT tools. Two online questionnaires were administered to 462 Turkish-speaking learners and 34 instructors. The results revealed that 94% of the learner participants reported using OMT tools for their language learning studies. The learners predominantly used these tools for single-word or phrase translations. Reading and writing assignments were the main areas where the learners most frequently referenced to OMT tools. The learner participants thought the accuracy of the tools was not high, and the ethicality of using them depended on how they were used. Three-quarters of the instructor participants reported using OMT tools, and their judgements concerning the accuracy of these tools were more positive than the learners’. The results also revealed a mismatch between learners’ and instructors’ perceptions and attitudes regarding OMT tools in foreign language learning. Accordingly, the instructors often overestimated how much learners use OMT tools, while learners underestimated the instructors’ interest in them. These findings suggest policies should be developed within language learning institutions to guide students’ use of OMT tools, as well as improve the mutual understanding between students and teachers in terms of their ethicality.

Next Generation Mobile Learning: Leveraging Message Design Considerations for Learning and Accessibility

Online machine translation (OMT) tools are not exclusively designed for language learners; however, these tools are popular among them. This quantitative study investigated the perceptions and attitudes of Turkish speaking EFL learners and instructors in a university English program regarding the use of OMT tools. Two online questionnaires were administered to 462 Turkish-speaking learners and 34 instructors. The results revealed that 94% of the learner participants reported using OMT tools for their language learning studies. The learners predominantly used these tools for single-word or phrase translations. Reading and writing assignments were the main areas where the learners most frequently referenced to OMT tools. The learner participants thought the accuracy of the tools was not high, and the ethicality of using them depended on how they were used. Three-quarters of the instructor participants reported using OMT tools, and their judgements concerning the accuracy of these tools were more positive than the learners’. The results also revealed a mismatch between learners’ and instructors’ perceptions and attitudes regarding OMT tools in foreign language learning. Accordingly, the instructors often overestimated how much learners use OMT tools, while learners underestimated the instructors’ interest in them. These findings suggest policies should be developed within language learning institutions to guide students’ use of OMT tools, as well as improve the mutual understanding between students and teachers in terms of their ethicality.

Эффективность систем машинного перевода в урбанистическом дискурсе

This article aims to analyze the use of Yandex.Translate, an online machine translation system, in translating urban discourse texts on the web. The authors use integrative linguistic-and-pragmatic approach to assess machine translation quality in a global digital setting. The aim is to show the efficiency of a state-of-the-art machine translation system and to investigate its usefulness in practical application. The authors perform a detailed analysis of the Paris city website content, which is automatically translated from French into Russian with Yandex.Translate. The data selection is justified by the absence of official foreign versions of this website, which points to the need of machine translation engines integrated in a web browser. Less than 20% of the analysed machine-translated texts demonstrate high language quality, whereas 60% can be referred to as acceptable – the text preserves the meaning of the source but contains some errors and inaccuracies in the target language. About 20% of the machine-translated text contains blunders, which violate Russian language norms. It causes source text contents distortion and communication failures. In the end, a classification of the system errors is presented. It is also concluded that machine translation would substitute middle-skilled human translators in the future. However, the use of such systems will enforce standardisation and simplification of the target language.

Translating Malay Compounds into Arabic Based on Dynamic Theory and Arabization Method

This study aims at making possible the effective use of machine translation (MT) in interpreting the Malay compounds into Arabic ones following the structure and Arabic style. The necessity of this study arises on account of the weakness of translation quality using online MT and the lack of suitable methods to structure the compounds from the Malay language into Arabic. There are three objectives of this study which are to collect the results of Malay compound translations using online MT into Arabic, analyze the results of the compound translations, and suggest compound translation methods based on dynamic theory and Arabization method. The study uses three online MT as instruments to translate: Google Translate, Microsoft Bing Translator, and Yandex Translator. This qualitative study employs a descriptive approach and analysis method in collecting information and analyzing data. The study focuses on 15 Malay compounds which are later categorized into school names, hospital names, and clinics. The findings of translation have been drawn using the next three MTs and analyzed at three main level: namely grammar level, phonetics and phonology level, and dynamic translation level. From this analysis, 4 out of 15 compound nouns translations data into Arabic are categorized as poor translations for not approaching the structure and Arabic style. In the final stages, the results of the translation collected are formulated and suggested alternative translations based on dynamic theory and methods of Arabization and compound restructuring formula in Arabic. Through this process, the translation results of the compounds can be categorized as translations that can meet the structure and style of the Arabic language. The compound translation model can be proposed as a new translation method for Arabic language users, especially the Arabic translators and students both at school and higher education.

Considering Machine Translation (MT) as an Aid or a Threat to the Human Translator:

The present study aims to evaluate the output quality of an online MT; namely, Google Translate, from English into Persian and compare its output with the translations made by the human translators to find out that whether MT applications are considered as an aid or a threat to human translators. For the application of the study, the researcher designed a translation test consisting of 60 statements from different types of texts proposed by Reiss (1989). The translation test was translated via Google Translate and administrated to three human translators to be rendered. The translations made by Google Translate and by the three human translators alongside the 60 statements were given to 40 judges to be evaluated based on Dorr et al. s' (2010) criterion of MT quality assessment, including semantic adequacy, fluency, and understandability. As results indicated, Google Translate gave a good overall performance in the translation of the 60 statements into Persian in terms of semantic adequacy and understandability, but not in terms of fluency. Thus, there should be no fear of human translators being replaced by the MT. As conclusion, MT applications cannot be considered a threat to human translators, but as an aid for them. The present study also offers some recommendations that can be beneficial to translation students, trainee translators, translation teachers, and professional translators.

The effect of using machine translation on linguistic features in L2 writing across proficiency levels and text genres

Many studies that have investigated the educational value of online machine translation (MT) in second language (L2) writing generally report significant improvements after MT use, but no study as of yet has comprehensively analyzed the effectiveness of MT use in terms of various measures in syntactic complexity, accuracy, lexical complexity, and fluency (CALF). The present study examined how learners’ use of MT affects CALF measures in L2 writing using evaluations by automated computational tools as well as human raters. In addition, the study investigated whether proficiency level and text genre affect the learners’ use of MT. A total of 91 Korean learners of English participated in the main task of the study in which they wrote on an assigned topic in English first without the help of any resource, and then on a different topic using only Google Translate a week later. Text analysis of students’ writing revealed major improvements in accuracy but unclear benefits in syntactic and lexical complexity. It was also found that MT use provided different advantages and disadvantages depending on the proficiency level (high vs. low) and text genre (narrative vs. argumentative). Survey responses strongly indicated that students are highly satisfied with MT and plan to use it again in the future despite being aware of its limitations. Overall, this study found that MT can be useful for improving accuracy but must be used with much discretion for it to benefit other aspects of L2 writing.

Exploring the use of online machine translation for independent language learning

The free availability of online machine translation (OMT) on the Internet via computers, tablets and smartphones makes it convenient for use by language students of all levels. Google Translate has been widely listed as an independent language learning (ILL) resource and we cannot deny its role for ongoing education. We are aware of the fact that this developing piece of technology was not designed with language learning in mind and, as a consequence, has limited current abilities depending on the language pair, language direction, genre, etc. However, as educators, we cannot help but wonder how the students use it independently and what pedagogical implications this may have in the language class. This study sets to analyse how language learners assess the usefulness of machine translation output and what they think about the use of OMT (in combination with other online language resources) for oral and written comprehension and production (e.g. writing and translation). This will help determining whether its use by language learners can be counterproductive or whether, if used wisely, can assist ILL and help boosting language instant communication.

Chinese speakers’ use of machine translation as an aid for scholarly writing in English: a review of the literature and a report on a pilot workshop on machine translation literacy

ABSTRACT With the introduction of free online machine translation tools, and particularly following the integration of artificial neural networks into this technology, there has been a growing interest in exploring the potential of machine translation as an aid for writing in another language. This article synthesizes the literature that focuses specifically on the use of machine translation by Chinese speakers who seek to write in English in a scholarly context. This article also reports on a pilot study carried out with international students from China at a Canadian university. The students participated in a machine translation literacy workshop where they learned tips to use this technology more effectively to help them with writing in English. Overall, the workshop was a success with students reporting increased knowledge about and confidence in using machine translation; however, they also suggested that future iterations of the workshop could be improved by adding more language-pair specific tips for translation-friendly writing, as well as more information on post-editing the Chinese-English language pair.

기계번역에 관한 KCI 연구논문 리뷰 : 인문학 저널 논문(2011∼2020년 초)의 논의내용과 연구방법을 중심으로

This study reviews articles about “machine translation” from Arts and Humanities journals covered in KCI-Journal Database between 2011 and early 2020. It examines a total of 121 articles in two stages. First, it reveals six major topics addressed in the previous works, namely “errors in machine translation,” “machine translation versus human translation” (and “comparison of translation machines”), “linguistic analysis of machine translation,” “perceptions of free online machine translation (FOMT),” “translation machines as an educational tool,” and “machine translation post-editing and pre-editing.” Second, this study reviews the 121 articles in terms of the “nature of research (conceptual research versus empirical research)” and “research method” (as a comprehensive notion, including “participants,” “material,” “translation machines,” “language pairs,” and “directionality in translation”). The study also discusses limitations of the previous studies and areas in which future researchers could build on previous findings.

Online Machine Translation: The Students’ Perspective during Quarantine Period Learning Activity

The role of internet nowadays leads to the increase of online translation usage. The online translation offers various kinds of machine translation besides the-popular- Google Translate. The purpose of this research is to determine the students’ perspective on online machine translation they can easily found on internet related to the learning process on translation study during the quarantine period.. The research questions are; 1) What are the good sides of using online machine translation? 2)What are the shortages of using online machine translation? 3)How does online machine translation help students during learning activities on quarantine period? Online machine translation is automated translation or “translation carried out by a computer” with the internet connection. The subjects of this study were 6th semester students at English Literature Department of Universitas Ngudi Waluyo who had taken subjects related to translation. The research was conducted by delivering survey with google form to gather students’ perspectives. From the results, it is concluded that students were familiar with Google Translation as the online machine translation. Students stated that online machine translation often gives ambiguous translation. The use of online machine translation is helpful especially in terms of saving time. In conclusion, to keep up with the development of digital era, students need to be introduced to various online machine translation to help them work faster and keep improving their translation skill to back up the defects of online machines translation.

한-영 신문사설 번역에서 나타나는 인간번역과 기계번역 간의 어휘 사용 차이 연구

This study aims to identify stylistic differences between human and machine translation in terms of word usage. For this purpose, a comparable corpus was constructed, which consisted of English translations of 110 Korean newspaper editorials done by a group of human translators and three online machine translation services (Google, Bing and Papago) respectively. Principal component analysis was performed on the corpus to investigate differences in the way 200 most frequent terms are related to the human and machine translators. Additionally, part-of-speech analyses were carried out to further elucidate the differences found in the PCA analysis. The major findings are that machine translators tend to overuse ‘be’ verbs and ‘as’ and ‘if’ subjunctive connectives, while underusing third-person personal pronouns, particularly the female form, ‘she’. Additionally, they were found to rely heavily on high-frequency content words. These characteristics of machine translators are construed as stemming from their scope of lexical options being limited by structural correspondence to original Korean texts.

Teaching Arabic Machine Translation to EFL Student Translators: A Case Study of Omani Translation Undergraduates

The present paper describes a machine translation (MT) course taught to undergraduate students in the Department of English Language and Literature at Dhofar University in Oman. The course is one of the major requirements for BA in Translation. Fifteen EFL translation students who were in their third year of study were enrolled in the course. The author presents both the theoretical and practical parts of the course. In the theoretical part, the topics covered in the course are outlined. As for the practical part, it focuses on the translation students’ post-editing of online MT output. This is beneficial to the students as free online MT systems can potentially be used as a means for improving student translators’ training and EFL learning. This is achieved through subjecting MT output to analysis or post-editing by the students so that they can focus on the differences between the source and target languages. With this goal in mind, assignments were given to the students to post-edit the Arabic and English MT output of three free online MT systems (Systran, Babylon and Google Translate), discuss the linguistic problems that they spot for each system and choose the one that has the fewest number of errors. The results show that the students, with varying degrees of success, have managed to identify some linguistic errors with the MT output for each MT system and thus produced a better human translation. The paper concludes that there is a need to incorporate MT courses in translation departments in the Arab world, as integrating technology into translation curricula will have great effect on student translators’ training for their future career as professional translators.

Comparative Research on C-E Online Machine Translation and Human Translation: Case Studies about the English Version of Report on the Work of the Government (2018) and the Version from Two Online MT Tools

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Quality and Machine Translation: An Evaluation of Online Machine Translation of English into Arabic Texts

This study compares the translation outputs of an English into Arabic text using the three machine translators of Google Translate, Microsoft Bing, and Ginger. To carry this evaluation of the machine translation (MT) outputs, an English text and its Arabic counterpart were selected from the UN records. The English source text was segmented into 84 semantic chunks. Depending on the Arabic counterpart model text, each chunk was rated as “correct or incorrect” at the two levels of the translation attributes: fidelity and intelligibility. To perform the quantitative description of the evaluation process, the numbers of fidelity and intelligibility errors and their percentages were calculated. Results of this evaluation process revealed that none of the three translated versions of the source text was perfectly translated. Although the translation of Microsoft Bing was rated the best, Google’s translation was found the least accurate due to the high percentage of fidelity and intelligibility errors detected in its translation output. However, the quality of Ginger’s translation was found slightly less accurate than that of Microsoft Bing, but remarkably better than Google’s translation. The findings of this study imply that these MT applications can be implemented to perform English into Arabic translation to get the broad gist of a source text, but a deep and thorough post-editing process looks essential for a full and accurate understanding of an English into Arabic MT output. The study recommends that more studies are encouraged to continue to assess the quality of MT that will further highlight its weaknesses and the strategies that should be adopted to overcome them.

한국어 학습자의 온라인 기계번역 도구 사용 경험 및 태도에 관한 연구 - 초급 및 중급 학습자를 대상으로 -

The purpose of this study is to examine the experience and attitude of Korean learners about using online machine translation tools. To accomplish this goal, 99 Korean learners of elementary and intermediate level were surveyed and their results were analyzed by each item. As a result, most Korean learners have experienced using machine translation tools in Korean language learning, and have found that a large part of Korean language learning relies on the use of machine translation tools. However, it was still recognized that the use of machine translation tools was an auxiliary means of Korean language learning. For some items, there was a difference in response outcome by proficiency. There was a significant difference between the types of machine translation tools used, the purpose of using machine translation tools, and the degree of dependence on machine translation tools. The results of this study showed that Korean learners have some experience and awareness about online machine translation tool. Also, we could see how these experiences and attitude differ according to learners’ level. This study has significance in that it is the first attempt as a specific research study on this field.

Design and Development of a Large Cross-Lingual Plagiarism Corpus for Urdu-English Language Pair

Cross-lingual plagiarism occurs when the source (or original) text(s) is in one language and the plagiarized text is in another language. In recent years, cross-lingual plagiarism detection has attracted the attention of the research community because a large amount of digital text is easily accessible in many languages through online digital repositories and machine translation systems are readily available, making it easier to perform cross-lingual plagiarism and harder to detect it. To develop and evaluate cross-lingual plagiarism detection systems, standard evaluation resources are needed. The majority of earlier studies have developed cross-lingual plagiarism corpora for English and other European language pairs. However, for Urdu-English language pair, the problem of cross-lingual plagiarism detection has not been thoroughly explored although a large amount of digital text is readily available in Urdu and it is spoken in many countries of the world (particularly in Pakistan, India, and Bangladesh). To fulfill this gap, this paper presents a large benchmark cross-lingual corpus for Urdu-English language pair. The proposed corpus contains 2,395 source-suspicious document pairs (540 are automatic translation, 539 are artificially paraphrased, 508 are manually paraphrased, and 808 are nonplagiarized). Furthermore, our proposed corpus contains three types of cross-lingual examples including artificial (automatic translation and artificially paraphrased), simulated (manually paraphrased), and real (nonplagiarized), which have not been previously reported in the development of cross-lingual corpora. Detailed analysis of our proposed corpus was carried out using n-gram overlap and longest common subsequence approaches. Using Word unigrams, mean similarity scores of 1.00, 0.68, 0.52, and 0.22 were obtained for automatic translation, artificially paraphrased, manually paraphrased, and nonplagiarized documents, respectively. These results show that documents in the proposed corpus are created using different obfuscation techniques, which makes the dataset more realistic and challenging. We believe that the corpus developed in this study will help to foster research in an underresourced language of Urdu and will be useful in the development, comparison, and evaluation of cross-lingual plagiarism detection systems for Urdu-English language pair. Our proposed corpus is free and publicly available for research purposes.

The Varibility of Reproduction: Emotive Units in a Literary Text (On the material of Ukrainian, Russian and Chinese) Variation of reflection of English-speaking emotional units in the translation of an artistic work (in Ukrainian, Russian, Chinese)

The article is focused on peculiarities of English and Chinese political discourse translation into Ukrainian. The advantages and disadvantages of machine translation are described on the basis of linguistic analysis of online Google Translate and M-Translate systems. The reasons of errors in translation are identified and the need of post-correction to improve the quality of translation is wanted. Key words: political discourse, automatic translation, online machine translation systems, machine translation quality assessment.

Machine Translation for EFL

This paper reports on an ongoing study into the affordances of free online machine translation for students learning English as a foreign language (EFL) at the tertiary level in Japan. The researchers are currently collecting data from a questionnaire, task performance, and interviews with 10-15 EFL learners in an English Language Institute in a university in Japan. The paper provides some background on the changing role of translation in language learning theory and pedagogy, before focusing literature related to technical developments in machine translation technology, and its application to foreign language learning. An overview of the research methodology is provided, along with some insights into potential findings. Findings will be presented in subsequent publications.