Comparing machine translation and human translation for South African languages

The article provides a comparative analysis of 27 studies carried out over the last five years on the use of information and communication technologies (ICT) in education, the application of ICT in education and the utilisation of machine translation (MT) in the teaching of foreign languages and translation. It outlines the trends identified by these studies, the achievements to date and the most promising areas for further research. The main areas identified were: the theoretical justification for the use of ICT; the comparative effectiveness of different MT systems, on the one hand, and human translators, on the other; the assessment of students’ target texts taking into account their degree of independence from MT; the role of post-editing in the teaching of foreign languages and translation and the methodology of its application in the teaching process; the role of ICT in the translation industry and its impact on the content of training programmes and curricula for future translators. The analysis showed that there is a considerable lack of sufficient research in the first area, as well as contradictory results in the remaining three (discrepancies in the evaluation of the translation efficiency of different MT systems and of MT compared to humans; unavailability of an effective and economical methodology for the evaluation of texts produced with the use of MT; the absence of a rational methodology for the application of post-editing at different stages of training and under different conditions). The author highlights the positive attitude of the translation industry towards ICT and the significant gap between its needs and the content of the training of future translators. The most promising directions for further research are outlined. These include, in particular: developing a methodology for the formation of skills included in the model of technological competence of a future translator; clarifying the comparative effectiveness of different MT systems and their potential areas of application; specifying the differences between machine and human translation and determining their optimal correlation in translator training and translation practice; identifying the optimal proportion of MT in the content of translator training and ways of evaluating texts translated using MT; developing a model for the effective integration of post-editing into the content of training; investigating ways of increasing the influence of the translation industry on the content of translator training.

PurposeHow closely does the translation match the meaning of the reference has always been a key aspect of any machine translation (MT) service. Therefore, the primary goal of this research is to assess and compare translation adequacy in machine vs human translation (HT) from Arabic to English. The study looks into whether the MT product is adequate and more reliable than the HT. It also seeks to determine whether MT poses a real threat to professional Arabic–English translators.Design/methodology/approachSix different texts were chosen and translated from Arabic to English by two nonexpert undergraduate translation students as well as MT services, including Google Translate and Babylon Translation. The first system is free, whereas the second system is a fee-based service. Additionally, two expert translators developed a reference translation (RT) against which human and machine translations were compared and analyzed. Furthermore, the Sketch Engine software was utilized to examine the translations to determine if there is a significant difference between human and machine translations against the RT.FindingsThe findings indicated that when compared to the RT, there was no statistically significant difference between human and machine translations and that MTs were adequate translations. The human–machine relationship is mutually beneficial. However, MT will never be able to completely automated; rather, it will benefit rather than endanger humans. A translator who knows how to use MT will have an opportunity over those who are unfamiliar with the most up-to-date translation technology. As MTs improve, human translators may no longer be accurate translators, but rather editors and editing materials previously translated by machines.Practical implicationsThe findings of this study provide valuable and practical implications for research in the field of MTs and for anyone interested in conducting MT research.Originality/valueIn general, this study is significant as it is a serious attempt at getting a better understanding of the efficiency of MT vs HT in translating the Arabic–English texts, and it will be beneficial for translators, students, educators as well as scholars in the field of translation.

Post-editing has become an important part not only of translation research but also in the global translation industry. While computer-aided translation tools, such as translation memories, are considered to be part of a translator's work, lately, machine translation (MT) systems have also been accepted by human translators. However, many human translators are still adopting the changes brought by translation technologies to the translation industry. This paper introduces a novel approach for seeking suitable pairs of n-grams when recommending n-grams (corresponding n-grams between MT and post-edited MT) based on the type of text (manual or administrative) and MT system used for machine translation. A tool that recommends and speeds up the correction of MT was developed to help the post-editors with their work. It is based on the analysis of words with the same lemmas and analysis of n-gram recommendations. These recommendations are extracted from sequence patterns of the mismatched words (MisMatch) between MT output and post-edited MT output. The paper aims to show the usage of morphological analysis for recommending the post-edit operations. It describes the usage of mismatched words in the n-gram recommendations for the post-edited MT output. The contribution consists of the methodology for seeking suitable pairs of words, n-grams and additionally the importance of taking into account metadata (the type of the text and/or style and MT system) when recommending post-edited operations.

Since Google introduced the Transformer model into natural language processing (NLP) in 2017, AI-aided translation has rapidly advanced. At the same time, translation is evolving from a solitary endeavor into a cooperative activity between human translators and machine translation systems, epitomized by the emergency of platforms with the Machine Translation Post Editing (MTPE) function. The advent of new translation modes also leads to increased research evaluating the effectiveness and quality of machine translation, for example, studies on the translation quality under the Multidimensional Quality Metrics (MQM) error typology framework. Involving AI-based translators and MTPE in their translation enables human translators to prepare the engineering documents efficiently. However, researchers notice that it is difficult for most machine translators to figure out the semantic and cultural differences in the source language and generate coherent structural translation in the target language. This research opens up ChatGPTs application in tender document translation under the MQM framework, hoping to cast light on assessment on ChatGPT's translation quality, identification of ChatGPT's errors in translating such documents and suggestions on human translators' performance throughout MTPE.

INTRODUCTION Expert human translation still surpasses the best results of machine translation (MT) systems (Bar-Hillel, 2003), but it is often hard to schedule an interpreter at the spur of the moment, especially for relatively obscure languages. Several free, fully automatic, Web-based translation services are available to fill this need but at the expense of lower accuracy. However, many translations do not need to be perfect. For example, a reader of a Web page or an email message written in a foreign language might need to get only the gist of the passage before deciding whether more detailed, human translation is needed or the content is not important enough to proceed further with it. That is, poor accuracy quickly can have greater value than higher accuracy that is too late (Muegge, 2006). As a result, more words are now translated per year using MT than are translated by human translators, and the demand continues to grow (LISA, 2009). Few studies have been conducted on the relative accuracies of these Web-based services, however. The purpose of this paper is to provide a performance overview of four leading MT systems provided on the Web and to further assess the accuracy of the best. Prior Studies of Web-Based MT Systems Machine translation was first proposed in 1947, and the first demonstration of a translation system was in January 1954 (Hutchins, 2003). MT became available for personal computers in 1981, and in 1997, Babel Fish (using SYSTRAN) appeared as the first, free, translation service on the World Wide Web (Yang & Lange, 1998). Although several evaluation studies have been conducted on MT systems (e.g., NIST, 2008), based upon an extensive review of the literature, only a few have focused solely upon Web-based versions. For example, four have tested the accuracy of SYSTRAN (originally provided at http://babelfish.altavista.com/babelfish-now: http://babelfish.yahoo.com/): Study 1 (Aiken, Rebman, Vanjani, & Robbins, 2002): In one of the earliest studies of a Web-based MT system, four participants used SYSTRAN to automatically translate German, French, and English comments in an electronic meeting. After the meeting, two objective reviewers judged the overall accuracy of the translations to be about 50% while the understanding accuracy was about 95%. Study 2 (Aiken, Vanjani, & Wong, 2006): In another study, a group of 92 undergraduate students evaluated SYSTRAN translations of 12 Spanish text samples to English, and they were not able to understand only two of the 12 translations (83% accuracy). No significant differences in understandability were found based on gender, but those who reported understanding some Spanish were able to understand many of the translations to English better. Further, the accuracy did not seem to correlate with the complexity of the sentences. Study 3 (Yates, 2006): In a third study, 20 sentences (10 Spanish, 10 German) selected from Mexican and German civil codes and press releases from foreign ministries were translated to English with SYSTRAN, and the author evaluated the samples' accuracies. The system's performance was rated as poor, but it was not uniformly poor, i.e., German texts were translated less poorly than the Spanish ones. Study 4 (Ablanedo, Aiken, & Vanjani, 2007): In a final study, 10 English text samples were translated by an expert and an intermediate-level Spanish translator as well as SYSTRAN. The most fluent human was 100% accurate, and the other achieved 80% accuracy. The MT system achieved only 70% accuracy but was 195 times faster than the humans. All of these tests were based upon SYSTRAN, the system deemed most reliable at the time of the studies. However, new translation software on Google appeared in October 2007. Abandoning the rule-based algorithms of SYSTRAN which the site had used previously, Google Translate (http://translate. …

Human language technology (HLT) contributes to the development of languages by providing various avenues through which languages can be interrogated. Through HLT, diverse questions can be raised and answered scientifically and objectively. In the context of South African indigenous languages (SAIL), several HLT tools support these languages. However, it seems that some language users are unaware of the availability and capabilities of these tools, which contributes to their underutilisation. This study aims to identify and describe briefly some of the HLT tools that support and analyse SAIL. It presents an overview of the open access HLT tools, namely part-of-speech (POS) taggers, morphological decomposers (MDs), morphological analysers (MAs), isiZulu.net, ZulMorph and Google Translate (GT). These tools are crucial in analysing and understanding SAIL, as well as for advancing these languages in the field of HLT. In this study, the researchers anticipate that by raising awareness of the existence of these tools, more users of indigenous languages will be eager to use them.Contribution: This study fills the practical gap in the use of HLT to perform linguistic functions for SAIL. It seems that there is underutilisation of existing HLT tools for SAIL, which might be attributed to language users being unaware of these tools. Therefore, the study aims to identify and describe some HLT tools that support and analyse SAIL. It presents an overview of the open access HLT tools, namely POS taggers, MD, MA, isiZulu.net, ZulMorph and GT. The researchers intend to demonstrate the use of these tools and to raise awareness about their existence.

Most local public health departments serve limited English proficiency groups but lack sufficient resources to translate the health promotion materials that they produce into different languages. Machine translation (MT) with human postediting could fill this gap and work toward decreasing health disparities among non-English speakers. (1) To identify the time and costs associated with human translation (HT) of public health documents, (2) determine the time necessary for human postediting of MT, and (3) compare the quality of postedited MT and HT. A quality comparison of 25 MT and HT documents was performed with public health translators. The public health professionals involved were queried about the workflow, costs, and time for HT of 11 English public health documents over a 20-month period. Three recently translated documents of similar size and topic were then machine translated, the time for human postediting was recorded, and a blind quality analysis was performed. Seattle/King County, Washington. Public health professionals. (1) Estimated times for various HT tasks; (2) observed postediting times for MT documents; (3) actual costs for HT; and (4) comparison of quality ratings for HT and MT. Human translation via local health department methods took 17 hours to 6 days. While HT postediting words per minute ranged from 1.58 to 5.88, MT plus human postediting words per minute ranged from 10 to 30. The cost of HT ranged from $130 to $1220; MT required no additional costs. A quality comparison by bilingual public health professionals showed that MT and HT were equivalently preferred. MT with human postediting can reduce the time and costs of translating public health materials while maintaining quality similar to HT. In conjunction with postediting, MT could greatly improve the availability of multilingual public health materials.

Intricacies concerning indigenous languages in the South African milieu demonstrate intransigence that necessitates a scholarly contestation. This is in addition to the parades that have been made by the post-colonial government and language experts to ennoble the stature of these indigenous languages. With that context, this article underscores the historical component of indigenous languages and retainment strides - including challenges – that have been underlined in respect of South African indigenous language matters. The objective, among others, is to underscore those challenges concerning indigenous African languages, and in particular, South African indigenous languages exhibit tenacity. To ratify the claims of the article, a systemic literature review is appreciated as a fragmentary qualitative research methodology while conceptualization of language matters in South Africa couches the theoretical underpinnings. The principal discussion is that challenges that prevail within the phenomenon of language in the South African context must be acknowledged in a bid to solicit reasonable solutions to the problematized phenomenon. For future scholarly implications, it is debated that indigenous language matters must be contested.

Even though machine translation (MT) systems have shown promise for automatic translations, the quality of translations produced by MT systems is still far behind professional human translations (HTs), because of the complexity of grammar and word usage in natural languages. As a result, HTs are still commonly used in practice. Nevertheless, the quality of HTs is strongly depending on the skills and knowledge of translators. How to measure the quality of translations produced by MT systems and human translators in an automatic manner has faced a lot of challenges. The transitional way to manually checking the accuracy of translation quality by bilingual speakers is expensive and time-consuming. Therefore, we propose an unsupervised method to assess HTs and MTs quality without having access to any labelled data. We compare a range of methods which are able to automatically grade the quality of HTs and MTs, and observe that the Bidirectional Minimum Word Mover’s Distance (BiMWMD) obtains the best performance on both HTs and MTs dataset.

This article discusses Antjie Krog's translation of verse written in the indigenous South African languages in the anthology Met woorde soos met kerse [“With words as with candles”] into Afrikaans. It looks at Krog's work as a translator as well as her ideas about translation as a means of empowering the speakers and writers of languages smaller and institutionally less powerful than English and Afrikaans in South Africa. The translations in Met woorde soos met kerse are discussed against the background of Lawrence Venuti's view of translation as a practice in which processes of “domestication” are set off against processes of “foreignization”. Venuti maintains that the translator inscribes the foreign text with domestic intelligibilities and interests, drawn from the receiving language and culture, to enable the foreign text to be received there. Because of this, he also argues for a need to preserve the foreignness of the foreign text in order that the hierarchies that rank values in the domestic culture can be “disarranged to set going processes of defamiliarization, canon formation, ideological critique, and institutional change”. The article tries to demonstrate that Krog's translation of the foreign texts (the poems in South Africa's indigenous African languages) domesticates them in various ways, while at the same time foregrounding their foreignness in such a way that it promotes transformation and change in the domestic culture (the literary system and culture of Afrikaans).

Indigenous languages in South Africa must be preserved to ensure that they do not lose their identity and become extinct. The four indigenous languages with the fewest speakers among South Africa’s 12 official languages are: Xitsonga, Siswati, Tshivenḓa and isiNdebele. The preservation of these languages in South Africa has been a long-standing challenge because of various social and economic factors. With the advancement of technology, opportunities have arisen to preserve and promote the use of these languages. Therefore, this study explores various technological strategies that can be used to preserve the South African indigenous languages. These languages can be preserved by making them widely accessible to users through various strategies such as localisation of daily used technology, translation through crowdsourcing, digitisation and archiving. Digital learning tools such as machine translation (MT) and creating online dictionaries can also contribute to preserving these languages. Each of these strategies offers benefits on how technology could be employed effectively and facilitate the preservation of indigenous languages. This study demonstrates the significance of technology in preserving indigenous languages and promoting their use around the world.Contribution: This study fills the practical gap in the use of technology to adequately preserve minority indigenous languages of South Africa, namely, Xitsonga, Siswati, Tshivenḓa and isiNdebele. These languages do not receive much attention in terms of preservation using technology in South Africa. Therefore, the study provides practical technological strategies that need to be implemented to preserve the indigenous minority languages. The insight of this study into the use of technology to preserve South African languages fits well within the scope of Literator, which is to publish studies in linguistics and literature with a special focus on South African languages. This publication will bring solutions to how minority languages could be preserved in the context of South Africa.

Computer-aided Translation (CAT) tools have attracted the attention of scholars who practice translation in various disciplines. The current study investigated undergraduate students’ Perspectives on CAT tools and Machine Translation (MT). More specifically, it investigates to what extent CAT tools improve productivity and translation quality. Finally, it also explores the other merits of using CAT tools. The present study used a qualitative analysis and semi-structured interviews to answer the research questions. The findings indicate that most of the students have a positive attitude toward using CAT tools. Furthermore, the findings show that lexical, syntactic, and special use of expressions as well as collocations and words that have cultural connotations were the most challenging that the students encountered when using MT. in addition. Improving productivity, enhancing quality, scalability, and connectivity are the four concepts mentioned by the subjects of the study as merits that made them use the CAT tool for translation other than using machine translation.

Since the outbreak of COVID-19 towards the end of 2019 and its proliferation across the globe, the lives of many populations have been disrupted, causing intense turbulence in social, economic and political dimensions. With that in mind, this article reflects on and problematises the neglect of the indigenous South African languages by the national government in mainstream communications on COVID-19. Qualitative research inquiry is utilised to explore the importance of indigenous languages in South Africa’s healthcare system. By the same token, an attempt to underline some of the predominant challenges within the selected phenomenon is argumentatively presented using a scoping literature review as a research technique. The findings and discussions indicate that the desolation of indigenous South African languages can be regarded as a repetitive episode of the (post)colonial injustices pertaining to indigenous South African languages as well as the healthcare system. Thus, the concluding remarks emphasise the urgency of inculcating indigenous South African languages into all communication systems, with special reference to the healthcare system.

This paper presents the findings of a study conducted to investigate the impact of the adoption of the eleven official languages and related democratic policies on the production of books in indigenous languages as well as the role of public libraries in promoting the use of books written in indigenous languages. The study reveals that. despite the provisions of the New Constitution regarding language. it seems that the publishing houses have not made much effort to reduce the predominant status traditionally enjoyed by Afrikaans and English in the South African publishing industry. The findings also show that most libraries have collections published mainly in English and Afrikaans. In addition. it was found that books in indigenous languages made up less than 1% of the collections of most of the responding libraries. The results of this study portray a poor state of publishing in indigenous South African languages. It is recommended that every effort should be made to promote the use of these languages more widely and government support be solicited.

Language and culture are intimately connected thus we cannot understand culture without having direct access to its language. Learning a language therefore is equivalent to learning a particular society’s behaviour, culture and custom. Therefore it should be emphasised that language is culture and culture is language. How then can African indigenous law or African customary law be promoted within the law curriculum when South African indigenous languages are marginalised? The issue of the promotion of indigenous languages is a very contentious and crucial issue which also came to the fore during the Fees Must Fall Movement wherein academics were accused of being intellectually colonised. For instance student leaders echoed during their gatherings that “our academics are intellectually colonised; they are academic thugs” (Makelela 2018; 1). Thus the Fees Must Fall Movement as articulated by Makelela (2018; 2) “presents a continuation of an age-old struggle with more focus on the negative effects of corporate African universities, with issues around culture and language not explicitly stated”. This article reflects on the current situation with regard the teaching of African customary law and argues that the subject remains marginalised. The immediate impact of the state of affairs is that a form of injustice takes place when litigants affected by African customary law are before courts. This situation as emphasised in this article emanates from the fact that South African indigenous languages are marginalised thus resulting in the ultimate marginalisation of indigenous culture. The central argument of this article is that in the absence of a commitment to promote South African indigenous languages African customary law as a subject will not be fully beneficial to African indigenous people and various communities.