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The Value of Translation in the Era of Automation: An Examination of Threats

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Abstract

Starting from Goldberg’s (Antisocial media: Anxious labor in the digital economy, New York University Press, 2018) claim that the symbolic value attached to cognitive professions is threatened by automation, this chapter approaches the threat of automation and translator anxiety from a sociological perspective. The chapter highlights the task of “pattern recognition” in translation as an important factor related to the value of translation. The chapter argues that incompatibility between the nature of the task and Machine Translation (and related automated practices) is causing translator anxiety. This is supported by data from a focus group study that included 22 translation project managers working in Japan. Three concepts are addressed: morality, money, and suffering. The conclusion addresses the fact that the traditional value of translation will not align with the future of the translation industry, and scenarios of translators’ survival are explored.

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... For Miguel Angel Jiménez Crespo Exploring professional translators' attitudes towards control and autonomy in the human-centred AI era: quantitative results from a survey study Revista Tradumàtica 2024, Núm. 22 example, previous studies have shown that years of experience can correlate negatively with attitudes towards technologies (Sakamoto, 2020;Sakamoto et al., 2024) ...
... Here, fears about automation in and the encroachment of AI on the Miguel Angel Jiménez Crespo Exploring professional translators' attitudes towards control and autonomy in the human-centred AI era: quantitative results from a survey study Revista Tradumàtica 2024, Núm. 22 291 translation process can be perceived (Nunez Viera, 2020;Sakamoto, 2020;Sakamoto et al., 2024). This can be partly explained by previous studies showing that users might tend to perceive lower levels of control over newer technologies, such as new AI applications and technologies (e.g. ...
... Contrary to recent fears of automatisation (Sakamoto, 2020;Ragni and Viera, 2022), "algorithms" or "machines" represented only 6.12% of responses. Some responses included "do not know" or "unsure" (6.12%), while one respondent answered, "Not the machine!" ...
Article
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This paper presents a survey study on attitudes of US professional translators towards self-perceived “control” and “autonomy” regarding translation technologies. In the Human-Centered AI (HCAI) and “intelligence augmentation” paradigms, humans retain the highest possible levels of control and autonomy alongside high levels of automation. The rationale for this study is that the cycle of translation technology adoption normally implies human adaptation to technologies that have been previously developed without their input. This often leads to resistance to adoption and negative or divergent attitudes. Now that AI app integration is still at the early stages of development and adoption, it is of utmost importance to identify users’ needs and attitudes to develop tools that professionals can easily adopt and feel in control. Methodologically, the study involved a self-administered online Qualtrics survey that was responded by 41 US-based translators in May 2024. The results of the study show that the use of generative AI remains low, in line with other recent studies on the same subject. The self-reported levels of control and autonomy are nevertheless generally high, while subjects reported medium levels of forced technology use by external agents. Future expectations of control declined dramatically, but this perceived loss of control in the AI era was attributed to human agents in the process rather than AI apps or algorithms (big tech, developers, LSPs, project managers, clients, etc.). These low levels of sense of agency in the future correspond with recent studies that find that exploitation through “digital Taylorism” by other human agents might be perceived more of a threat than AI or translation technologies themselves.
... In order to support this growth, a skilled and motivated translator workforce is required. Yet, translators' working conditions seem to have been negatively affected by the industry's technology-led cost-cutting efforts, resulting in Sakamoto 2020). Our concern is that the current trends may cause a skills drain in the language industry, jeopardising the sustainability of the translator workforce and hindering the industry's healthy growth. ...
... The level of reliance on technology is high in the modern translation business, but individual translators' willingness to use technology varies greatly, affecting their work satisfaction (Ruokonen and Koskinen 2017). Technology is also one of the attributes of the increasing precariousness in translation profession (Moorkens 2017), impacting the perceived value of the profession (Sakamoto 2020). Machine translation (MT) has been the most prominent technology affecting translators' working practice with the rise of MTPE (machine translation post-editing). ...
... Task Satisfaction is defined as "the positive attitude experienced by a worker during, or upon completion, of a task" (Fisher 1980cited in Rodríguez-Castro 2015. Subscribing to the framework of two-factor theory (Herzberg 1959), Rodríguez-Castro (2015) suggests that, because of the satisfaction translators get from the task of translating, they may choose to continue to work as translators despite the recent adversarial working conditions (Moorkens 2017) and the anxiety they receive from the precarious professional status (Vieira 2018;Sakamoto 2020). In other words, they stay in the profession purely or predominantly due to the joy they receive from the task of translating itself, which may be a unique characteristic of translators. ...
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This article discusses the conceptual and methodological aspects of the Translator WRQoL (Work-related Quality of Life) survey and provides some preliminary results and observations based on the first pilot study. The survey is being developed to measure translators’ work satisfaction and motivation in the context of job digitalisation and automation. Literature suggests that translators’ work satisfaction and their career motivation have been adversely affected. The survey being developed in this study intends to quantitatively measure the causes of the adverse effects using psychometric-strong scales. The ultimate goal is to administer the Translator WRQoL survey on a large scale, and using SEM (Structural Equation Modelling), to identify the causal relationships between the constructs measured by the scale and to determine what kind of translators (regarding worker profiles and attitudes to technology and other factors) have high/low levels of work-related quality of life and are more/less willing to stay in the profession.
... SCOT originates in the field of Science and Technology Studies (STS) and is based on (a) the refusal of technological determinism and (b) the recognition of technological innovation as the result of a dynamic interplay between different social groups' interpretations of a technological artefact. Instances of practical applications of SCOT in Translation and Interpreting Studies are still rare, with Braun et al. (2018), Braun (2020), Sakamoto and Yamada (2020), and Sakamoto (2020) being some of the few exceptions. ...
... The use of SCOT in Translation and Interpreting Studies is still limited, with the exception of Braun et al. (2018), Braun (2020), Sakamoto and Yamada (2020). The framework has allowed to uncover themes such as the exclusion of interpreters' views from the process of technology implementation in Video-Mediated Interpreting (VMI) (Braun et al., 2018), and interpretative flexibility and potential closure mechanisms in MTPE (Sakamoto, 2020;Sakamoto & Yamada, 2020), overall highlighting how: the most important element for the successful design of technology is that the relevant groups […] enter into a meaningful dialogue to resolve misconceptions and construct a joint understanding of good practice in order to shape the technological artefact and associated practices in such a way that it is beneficial for all involved. (Braun, 2020, pp. ...
... In this respect, relevant social groups and interpretative flexibility emerge in relation to how literary translators perceive outsiders', researchers' and developers' narratives of literary translation as opposed to their own self-imaging strategies. Findings on the relation between self-image and attitudes towards technology echo those of Sakamoto (2020) and Sakamoto and Yamada (2020), where two categories of (non-literary) translators emerge from Translation Project Managers' narratives: the 'traditional' ones who prefer to translate from scratch and are held in higher regard by them, and the 'strange' ones, who prefer post-editing MT output instead and are somehow perceived as providing less effort and expertise to the job. This suggests that a parallel can be drawn between literary and non-literary translation, given that in the current study translation technology emerges as directly opposed to translators' views of their own profession. ...
Article
This paper reports findings and observations on using the Social Construction of Technology (SCOT) framework in a questionnaire study of literary translators’ self-imaging strategies and attitudes towards technology. The study took advantage of SCOT’s methodological flexibility to prioritise literary translators as a social group, hence compensating for the lack of opportunities to voice their interpretations of technology and become an active part in the framework’s development and implementation. Ultimately, the use (and adaptation) of SCOT proved useful for the identification, analysis, and discussion of recurrent themes in respondents’ narratives about technology and their position in society. In particular, SCOT helped to uncover the gap between how literary translators choose to (re)present themselves in society and how they see technology, and what other social groups might be pivotal for a more comprehensive, socially-relevant analysis. Finally, the paper presents suggestions for the use of SCOT in future research projects concerning the technologisation of the literary translation profession.
... First, with quality requirements lowered (see also Snell-Hornby 2006, 132 ff), particularly in cases where damages can be controlled, translators must adjust to neoliberal trends (see also Moorkens 2017). This demand can lead to epistemic dissonances, as translators lose the autonomy to determine the best solutions (see Almeida and O'Brien 2010), and axiological dissonances between their values and those of their environment regarding expertise, quality, and considerations of specific audiences (see also Sakamoto 2021). Additionally, feelings of alienation-the estrangement or separation of individuals from aspects of human nature due to living in a society structured around capitalism (Marx and Engels 1988)-can arise when translation is recast within Taylorist parameters (Moorkens 2020; see also Weil 1934Weil [1955, 140). ...
Chapter
This chapter reviews the social implications of machine translation (MT) and large language models (LLMs) through the lens of the ethics of care. Building on the issues addressed in the preceding chapters, it discusses how the development and deployment of MT technologies reinforce existing social hierarchies and geopolitical power dynamics. The chapter argues for expanding the public dimension of translation and interpreting studies (TIS) by incorporating an ethics of care to address the epistemological, technical, and phronetic challenges associated with MT. It proposes a strategic agenda for MT to become a more socially responsible tool, emphasizing the role of human translators and MT literacy in countering biases and misinformation. The chapter urges the translation community to reflect on its practices, contribute to societal well-being, and support equitable progress. It emphasizes the political dimensions of translation and the responsibilities of TIS in the era of AI.
... Despite the clear advantages provided by translation technologies, some language professionals seem to show some degree of aversion (Olohan 2020) and anxiety (Sakamoto 2021) to these. However, these attitudes are not linked with a luddite stance by language professionals, but with the question of "whether technologies substitute or complement workers, give rise to better or worse labour market conditions, and ultimately are associated with an increase or a decrease in labour market opportunities." ...
Chapter
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The ascent of neoliberalism and its policies has fuelled a surge in social and economic inequality across the global landscape. This trend extends its grip to the language services industry (LSI). Over the past 15 years, while companies within this sector have thrived and amassed wealth, translators and linguists have grappled with deteriorating working conditions. This paradox, which have been only recently considered by Translation Studies (TS), raises questions about the sustainability of the LSI and the livelihoods of its practitioners. In response to these concerns, this chapter focuses on three crucial phenomena shaping the global economy: the proliferation of non-standard employment arrangements, the dominance of labor monopsonies, and the transformative impact of technology on exacerbating precarity. Each of these is analysed from, among others, an economic, legal, and TS perspective. Various strategies are also outlined to counteract these neoliberal dynamics. Upon careful analysis, it becomes apparent that the sustainability of translation as a profession is under threat. Consequently, two courses of action are suggested. Firstly, TS should embrace a civil and social responsibility, guiding translators through these tumultuous times by adopting an industrial turn within the discipline. Secondly, translators must unite in collective action, advocating for informed policy-making processes aimed at safeguarding their interests.
... The advent of computers and AI heralded an advancement in translation with the development of MT systems (Poibeau, 2017). MT has the most significant potential to overcome language barriers and facilitate cross-lingual communication (Rivera-Trigueros, 2022) despite generating more nuanced findings on variations (Sakamoto, 2020). With this, research and advances in MTs have been expanding rapidly for several decades (Wang et al., 2022). ...
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Traditional views have long held that machine translation cannot achieve the quality and accuracy of human translators, especially in complex language pairs like Persian and English. This study challenges this perspective by demonstrating that ChatGPT-4, with access to vast amounts of multilingual data and leveraging advanced large language model algorithms, significantly outperforms widely utilized open-source machine translation tools and approaches the realm of human translation quality. This research aims to critically assess the translation accuracy of ChatGPT-4 against a traditional open-source machine translation tool from Persian to English, highlighting the advancements in artificial intelligence-driven translation technologies. Using Bilingual Evaluation Understudy scores for a comprehensive evaluation, this study compares the translation outputs from ChatGPT-4 with MateCat, providing a quantitative basis for comparing their accuracy and quality. ChatGPT-4 achieves a BLUE score of 0.88 and an accuracy of 0.68, demonstrating superior performance compared to MateCat, with a 0.82 BLUE score and 0.49 accuracy. The results indicate that the translations generated by ChatGPT-4 surpass those produced by MateCat and nearly mirror the quality of human translations. The evaluation demonstrates the effectiveness of OpenAI's large language model algorithms in improving translation accuracy.
... Although the naïve notion of machines inevitably replacing translators is virtually unsubstantiated, demanding empirical investigation, it may negatively affect translators' confidence in this age of automation (Sakamoto, 2021) or create uncertainty among some (Ehrensberger-Dow, 2021). In fact, the constant chatter about the potential impact of novel technologies on automating certain tasks, like translation-a topic frequently discussed on social media networks where people are actively exploring or experimenting with, for instance, the capabilities of AI dubbing-can erode translators' self-efficacy and their belief in their unique value as translators. ...
Article
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As technological developments, such as artificial intelligence or large language models, are rapidly transforming the profession of translation, the emotional vulnerability of translators has remained largely underexplored. Adopting vulnerability as a conceptual lens, this study examines the psychological and emotional experience of five Iranian translators working across diverse fields (e.g., subtitling and legal translation) and employment statuses (freelance, in-house, seasoned, or newbie) by analyzing data collected from oral and written narratives. Results suggested that technological developments in the translation industry create vulnerabilities in translators, triggering both positive emotions (admiration, excitement, satisfaction, and confidence) and negative emotions (uncertainty, frustration, anxiety, and fear). In other words, some translators experienced or perceived a sense of insecurity in certain scenarios, especially in the translation of academic and scientific content, where artificial intelligence is demonstrating particular capabilities. In contrast, some translators did not feel insecure about the rise of artificial intelligence; rather, they proactively embraced its potential and leveraged its capabilities to enhance their work.
... In contrast, AVT associations (ATRAE, 2021;AVTE, 2021;ATAA, 2022) are, as previously mentioned, mostly against MTPE as it is a process that affects the basics of AVT practice: quality. For their part, freelancers, often grouped under the umbrella of associations, face individual economic concerns and moral issues (Sakamoto, 2021). Finally, academia, which should be the first step in the process, always lags behind market needs (Gasparini et al., 2015). ...
Article
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La traducción automática y la posedición (TAPE) siguen considerándose, a menudo, enemigas de la libertad creativa tradicionalmente asociada al género audiovisual y a su traducción. El rechazo que su creciente presencia suscita entre gran parte de la comunidad profesional hace que la traducción audiovisual (TAV) no sea una de las disciplinas donde el uso de la TAPE se aborde abiertamente. Sin embargo, es necesario estudiar los beneficios de su implantación a todos los niveles, considerando todas las partes y a todos los implicados en el proceso.Con el fin de estudiar las diferencias entre el proceso tradicional de TAV –sin herramientas– y el proceso implementado con TAPE, se ha llevado a cabo un estudio piloto destinado a comparar los resultados en la traducción inglés-español de una serie de vídeos de noticias y deportes de 3 minutos de duración con diferentes características técnicas. Los resultados permitirán obtener una descripción comparativa objetiva de ambos procesos.
... As we mentioned, the advances in NMT architectures and domain adaptation techniques allowed for better performances in various domains. In the cultural sector, machine translation has mostly been used in the process of film subtitling, but a growing number of studies has focused on the challenges of its development, for instance, with literary texts (Sakamoto, 2020;Hansen, 2021). ...
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We present in this article what we believe to be one of the first attempts at video game machine translation. Our study shows that models trained only with limited in-domain data surpass publicly available systems by a significant margin, and a subsequent human evaluation reveals interesting findings in the final translation. The first part of the article introduces some of the challenges of video game translation, some of the existing literature, as well as the systems and data sets used in this experiment. The last sections discuss our analysis of the resulting translation and the potential benefits of such an automated system. One such finding highlights the model’s ability to learn typical rules and patterns of video game translations from English into French. Our conclusions therefore indicate that the specific case of video game machine translation could prove very much useful given the encouraging results, the highly repetitive nature of the work, and the often poor working conditions that translators face in this field. As with other use cases of MT in cultural sectors, however, we believe this is heavily dependent on the proper implementation of the tool, which should be used interactively by human translators to stimulate creativity instead of raw post-editing for the sake of productivity.
... Related to the explanation above, the researcher found that Jigsaw Teaching Technique has been used by many researchers and the research was successful. The successful research was written by Devi (Sakamoto, 2021). The result of her research show that using jigsaw technique is effective on students' reading comprehension at SMAN 1 Gurah. ...
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... Commonly, it is named information question. The question usually is formed by question word such as: what, where, why, who, which, When, whom, whose, how, and (3) Tag Questions (Sakamoto, 2021). Tag Questions are attached or tagged onto the ending of a declarative statement. ...
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... There are several arguments in favor of this position. First of all, there is no purpose in competing with NMT and it seems that translators are turning into transcreators to become the sort of translator who can produce high-quality translations which a machine can never produce (Sakamoto, 2021). Secondly, transitioning from translation to rehumanized value-added services such as transcreation seems to be not only a pragmatic decision in economic terms but also a way to move to more rewarding activities (Sosoni & Rogers, 2013). ...
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Transcreation is a creative adaptation service that has been studied from the perspective of the language services industry and academia. Despite broad interest in the topic, little is known about the perceptions individual professionals have of this practice. To fill this gap, this paper aims to provide information from this point of view and focuses on the economic characteristics of transcreation. For this purpose, a sociological study based on a survey has been carried out. A total of 360 professionals from all over the world participated in this initiative. The results show that transcreation is considered as a hard-to-automate service. The practice is perceived and paid as a value-added one, and it can be defined as a form of qualified craftsmanship. Likewise, it seems to be a better-paid service than others. Finally, transcreation is demanded not only by language service providers but also by companies in industries such as marketing, advertising, public relations, and communication.
... 33). According to A. Sakamoto [37], "[t]he fact that machines are increasingly outpacing humans-not always in terms of quality, but certainly in speed and volume-is one of the reasons. . .that translation is being devalued" (p. ...
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... English has a very important place and purpose in the world. As a result, English is extensively taught in a variety of nations worldwide (Sakamoto, 2021). The goal of English instruction in Indonesia is to help students become proficient in spoken and written English (Zahra et al., 2021). ...
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... As we mentioned, the advances in NMT architectures and domain adaptation techniques allowed for better performances in various domains. In the cultural sector, machine translation has mostly been used in the process of film subtitling, but a growing number of studies has focused on the challenges of its development, for instance, with literary texts (Sakamoto, 2020;Hansen, 2021). ...
Preprint
We present in this article what we believe to be one of the first attempts at video game machine translation. Our study shows that models trained only with limited in-domain data surpass publicly available systems by a significant margin, and a subsequent human evaluation reveals interesting findings in the final translation. The first part of the article introduces some of the challenges of video game translation, some of the existing literature, as well as the systems and data sets used in this experiment. The last sections discuss our analysis of the resulting translation and the potential benefits of such an automated system. One such finding highlights the model's ability to learn typical rules and patterns of video game translations from English into French. Our conclusions therefore indicate that the specific case of video game machine translation could prove very much useful given the encouraging results, the highly repetitive nature of the work, and the often poor working conditions that translators face in this field. As with other use cases of MT in cultural sectors, however, we believe this is heavily dependent on the proper implementation of the tool, which should be used interactively by human translators to stimulate creativity instead of raw post-editing for the sake of productivity.
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Recent research suggests that neural machine translation achieves parity with professional human translation on the WMT Chinese–English news translation task. We empirically test this claim with alternative evaluation protocols, contrasting the evaluation of single sentences and entire documents. In a pairwise ranking experiment, human raters assessing adequacy and fluency show a stronger preference for human over machine translation when evaluating documents as compared to isolated sentences. Our findings emphasise the need to shift towards document-level evaluation as machine translation improves to the degree that errors which are hard or impossible to spot at the sentence-level become decisive in discriminating quality of different translation outputs.
Article
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如果统计机器翻译(TAE) 是一种颠覆性新技术,那么神经元机器翻译(TAN)就可能是一个不断的持续性创新,它遵循了统计机器翻译的一贯路径,且它的评估方式起初与统计机器翻译基本一致。从这个角度来看,神经元机器翻译可以有效遏制统计机器翻译刚出现时的热度。
Article
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Translation is currently described as a profession under pressure from automation, falling prices and globalized competition. Translators' stance on machine translation (MT) is famously negative, but the economic dimension of this positioning is scarcely researched and often unclear. This article provides an analysis of translators' blog and forum postings contextualized within general trends in employment, the economy and work automation. The analysis concentrates on MT and pay. Two key findings are reported. First, MT was found to be a secondary issue in translators' comments on pay; most grievances were based on business practices themselves. Second, most criticisms of MT were rooted not in fears of being outperformed by MT systems, but rather in the technology's limitations and market consequences. This article calls for a broadening of translators' role across areas of specialization and argues that, in the debate on translation's future, MT cannot be decoupled from its economic effects.
Article
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Machine translation has made rapid advances in recent years. Millions of people are using it today in online translation systems and mobile applications in order to communicate across language barriers. The question naturally arises whether such systems can approach or achieve parity with human translations. In this paper, we first address the problem of how to define and accurately measure human parity in translation. We then describe Microsoft's machine translation system and measure the quality of its translations on the widely used WMT 2017 news translation task from Chinese to English. We find that our latest neural machine translation system has reached a new state-of-the-art, and that the translation quality is at human parity when compared to professional human translations. We also find that it significantly exceeds the quality of crowd-sourced non-professional translations.
Conference Paper
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We analyse posts on social media (Facebook, LinkedIn, and Twitter) as a means to understand how translators feel about machine translation (MT). A quantitative analysis of more than 13,000 tweets shows that negative perceptions outweigh positive ones by a ratio of 3:1 overall, and 5:1 in tweets relating MT to human translation. Our study indicates a disconnect between translation and research communities, and we outline three suggestions to bridge this gap: (i) identifying and reporting patterns rather than isolated errors, (ii) participating in evaluation campaigns, and (iii) engaging in cross-disciplinary discourse. Rather than pointing out each other's deficiencies, we call for computer scientists, translation scholars, and professional translators to advance translation technology by acting in concert.
Article
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In this article we present a corpus-based statistical approach to measuring translation quality, more particularly translation acceptability, by comparing the features of translated and original texts. We discuss initial findings that aim to support and objectify formative quality assessment. To that end, we extract a multitude of linguistic and textual features from both student and professional translation corpora that consist of many different translations by several translators in two different genres (fiction, news) and in two translation directions (English to French and French to Dutch). The numerical information gathered from these corpora is exploratively analysed with Principal Component Analysis, which enables us to identify stable, language-independent linguistic and textual indicators of student translations compared to translations produced by professionals. The differences between these types of translation are subsequently tested by means of ANOVA. The results clearly indicate that the proposed methodology is indeed capable of distinguishing between student and professional translations. It is claimed that this deviant behaviour indicates an overall lower translation quality in student translations: student translations tend to score lower at the acceptability level, that is, they deviate significantly from target-language norms and conventions. In addition, the proposed methodology is capable of assessing the acceptability of an individual student’s translation – a smaller linguistic distance between a given student translation and the norm set by the professional translations correlates with higher quality. The methodology is also able to provide objective and concrete feedback about the divergent linguistic dimensions in their text. © 2017 Artesis Hogeschool Antwerpen - Hoger Instituut voor Vertalers en Tolken. All rights reserved.
Article
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This paper discusses neural machine translation (NMT), a new paradigm in the MT field, comparing the quality of NMT systems with statistical MT by describing three studies using automatic and human evaluation methods. Automatic evaluation results presented for NMT are very promising, however human evaluations show mixed results. We report increases in fluency but inconsistent results for adequacy and post-editing effort. NMT undoubtedly represents a step forward for the MT field, but one that the community should be careful not to oversell.
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The profession of translation is undergoing enormous change, expedited by the global recession that began in 2007-200­8. Government policies and an intensive focus on cost has resulted in a large scale move to freelance or contingent work, leaving the worker in a precarious position with regard to rights and undermining his or her agency. This shift is exemplified particularly by the vendor model widespread in specialised translation work. Related to the downward pressure on costs and productivity is the technologisation of translation, with translation tools becoming a necessity and new use cases being found for post-edited and raw machine translation. Despite the recession, continued growth has been reported for the language industry, and the outlook for employment in translation is positive. This paper looks at the background to the economic and technological changes to translation, attempts to put them into a wider context, and looks to the options available to translators to maximise their agency within the ‘global value chain’. Translators have little option but to embrace new competences, but also need to focus on their expertise to maximise leverage and agency.
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Background: Using two researchers as independent instruments for interpretation in education policy evaluation, this study applies a collaborative grounded theory approach to qualitative data analysis and theory generation. Purpose: This study argues that varied perspectives should be a critical component in the methodological and analytical choices of education research, especially when the sought after outcome is deeper understanding of the impact, both positive and negative, of an education program or policy. In this study, rather than using one researcher to confirm the reliability of the other, the study explores the outcome of drawing on the positional reflexivity of two researchers, each with a distinct perspective, as a potential strength to co-generate themes and theory in the evaluation of complex policy or programs. Setting: The data for this analysis originated from interviews of education leaders (n = 13) from two states with contrasting approaches to teacher evaluation: Kentucky and California. Intervention: NA Research Design: Qualitative developmental evaluation Data Collection and Analysis: Semi-structured interviews and grounded theory coding Findings: Results suggest that more robust theory and analysis may result from independent thematic development and converged theory generation when working in a research team, as opposed to early application of inter-rater reliability. The reflexivity of different perspectives was, in part, reflexive of the self—their own biased perspective and prior experience. When merged, their joint interpretation may have unearthed greater dimensionality. Findings from this study can inform future strategies for evaluating qualitative research data, especially within a developmental evaluation approach aimed at understanding system complexity in education policy and practice.
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This paper focusses on the real problems involved in promoting the translator's role and status to that of intercultural mediator. Ever since the cultural turn in the 1980s, academics have been equating translation with intercultural mediation (IM) and translators as mediators. The paper first looks at how mediation has been understood in translation, and then investigates a number of issues regarding intervention, both at a theoretical and at a practical level. In theory, as a result of the cultural turn, there should be a more context-based understanding of communication, and hence a more intervenient role for the translator. At a practical level, however, normative roles follow a conduit theory of translation based on language transfer. While academia and the profession wrangle over IM, a number of other options are emerging to cater for the ever-increasing real need for translation and IM. This competition is potentially marginalizing translators and interpreters. It will be suggested that ‘transcreation’ may be a way forward, though optimism is tempered with the profession's own beliefs regarding intervention and towards change.
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The integration of data from statistical machine translation into translation memory suites (giving a range of TM/MT technologies) can be expected to replace fully human translation in many spheres of activity. This should bring about changes in the skill sets required of translators. With increased processing done by area experts who are not trained translators, the translator’s function can be expected to shift to linguistic postediting, without requirements for extensive area knowledge and possibly with a reduced emphasis on foreign-language expertise. This reconfiguration of the translation space must also recognize the active input roles of TM/MT databases, such that there is no longer a binary organization around a “source” and a “target”: we now have a “start text” (ST) complemented by source materials that take the shape of authorized translation memories, glossaries, terminology bases, and machine-translation feeds. In order to identify the skills required for translation work in such a space, a minimalist and “negative” approach may be adopted: first locate the most important decision-making problems resulting from the use of TM/MT, and then identify the corresponding skills to be learned. A total of ten such skills can be identified, arranged under three heads: learning to learn, learning to trust and mistrust data, and learning to revise with enhanced attention to detail. The acquisition of these skills can be favored by a pedagogy with specific desiderata for the design of suitable classroom spaces, the transversal use of TM/MT, students’ self-analyses of translation processes, and collaborative projects with area experts.
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In this paper we argue that the time is ripe for translator educators to engage with Statistical Machine Translation (SMT) in more profound ways than they have done to date. We explain the basic principles of SMT and reflect on the role of humans in SMT workflows. Against a background of diverging opinions on the latter, we argue for a holistic approach to the integration of SMT into translator training programmes, one that empowers rather than marginalises translators. We discuss potential barriers to the use of SMT by translators generally and in translator training in particular, and propose some solutions to problems thus identified. More specifically, cloud-based services are proposed as a means of overcoming some of the technical and ethical challenges posed by more advanced uses of SMT in the classroom. Ultimately the paper aims to pave the way for the design and implementation of a new translator-oriented SMT syllabus at our own University and elsewhere.
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This short article discusses the importance of prioritising cultural competence in technical translation. It emphasizes how cultural issues are inherent in technical texts and should not be overlooked, both in translation practice an in translation training.
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The main aim of this paper is to report on an online questionnaire which focused on translator and interpreter perception of their working world, their mindset or Weltanshauung , and the impact of Translation Studies and university training on that world. Questions, both closed and open-ended, addressed academic/professional training, present role(s) and attitudes and beliefs about ‘the profession’ itself. Nearly 1000 respondents replied to the questionnaire worldwide. Particular questions focused on how translation should be taught, the role and status of the profession (ideally and in practice), and on personal satisfaction. The results show that university training has had little impact, and that this group of respondents have relatively little interest in the university itself in comparison with lifelong learning, with most emphasis placed on practice and self-development. Members of the group feel themselves to be ‘professional’ due to their specialized knowledge and abilities. However, their professionalism is mainly limited to their responsibilities to the text itself, and there is relatively little interest in the wider context. They are acutely aware of the lack of public recognition, and both the interpreters and the translators agree that translators in particular suffer from a markedly lower social status. However, only a minority of the respondents feel the need to change the status quo and satisfy trait theory criteria regarding professional recognition, possibly because the vast majority of respondents are more than satisfied with their job. In conclusion, it appears that translation can still only be categorized as an occupation rather than as a profession, and it is suggested that a new role be created with its own university course to cater to the professional language provider.
Book
This book addresses popular and academic concerns that the institution of work is being irreparably damaged by digital/media technologies. The book considers three specific concerns (each in a separate chapter): 1) that all jobs may soon be automated out of existence, 2) that the sharing economy will degrade the few jobs that remain, and 3) that services like Facebook and Instagram are turning leisure into work, exploiting users in their so-called free time. Through an in-depth examination of these concerns, the book proposes that what really concerns these writers is not that work is being degraded or may soon disappear altogether, but rather that society itself is under attack, and more specifically the bonds of responsibility on which social relations depend. Drawing from recent work on affect/emotion and from the controversial antisocial thesis in queer theory, the book argues that the anxiety surrounding these transformations aims primarily not to slow or reverse these changes, but rather to solicit readers to identify with the social: to stop being irresponsible, unaccountable, lazy, self-serving, and hedonistic, and to once again engage in the hard work of being a productive member of society.
Article
More and more language service providers (LSPs) are now using a post-edited machine translation (PEMT) production model in addition to, or instead of, the traditional Translation-Editing-Proofreading (TEP) model, in order to cope with the growing demand for translation. As a result, translators are increasingly expected to work as post-editors in the PEMT process, but the reluctance of translators or resistance to this expectation is evident as they feel their professional skills and identities are sidelined by technology (Kelly 2014; Cadwell et al. 2017). This article attempts to provide a theoretical description of the translators' resistance to post-editing work using Bourdieu's concepts: capital, field and habitus. Bourdieu's sociological framework allows us to examine the positions of translators and post-editors in the field of translation and its mechanism of emotional impacts. For this purpose, I draw on qualitative and quantitative data collected in a focus group study with 16 UK translation project managers, a survey of 155 company websites and two training manuals for post-editors. The study will provide industry stakeholders, as well as translation educators, useful conceptualisation tools to understand the current situation surrounding social agency of translators and post-editors.
Article
As JoSTrans enters its fifteenth year of publication, this article sets out to chart how ‘specialised translation’ has been conceptualised since the journal’s launch based on a survey of articles published over that time. The results show a shift away from what has traditionally been considered as the core of specialised translation, namely, the interlingual translation of texts in non-fictional subject fields, with professional and training issues, as well as audiovisual translation now achieving higher numbers of articles. The inclusion of some literary topics, whilst not frequent, also suggests a broadly conceived publishing policy. The article concludes with an acknowledgment that a broader view of specialised translation can be productive in fostering new perspectives as part of the fast-changing interdiscipline of Translation Studies and in supporting flexible curriculum design.
Chapter
Given the rise of the new neural approach to machine translation (NMT) and its promising performance on different text types, we assess the translation quality it can attain on what is perceived to be the greatest challenge for MT: literary text. Specifically, we target novels, arguably the most popular type of literary text. We build a literary-adapted NMT system for the English-to-Catalan translation direction and evaluate it against a system pertaining to the previous dominant paradigm in MT: statistical phrase-based MT (PBSMT). To this end, for the first time we train MT systems, both NMT and PBSMT, on large amounts of literary text (over 100 million words) and evaluate them on a set of 12 widely known novels spanning from the 1920s to the present day. According to the BLEU automatic evaluation metric, NMT is significantly better than PBSMT (p < 0.01) on all the novels considered. Overall, NMT results in a 11% relative improvement (3 points absolute) over PBSMT. A complementary human evaluation on three of the books shows that between 17% and 34% of the translations, depending on the book, produced by NMT (versus 8% and 20% with PBSMT) are perceived by native speakers of the target language to be of equivalent quality to translations produced by a professional human translator.
Chapter
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.
Conference Paper
For machine translation to tackle discourse phenomena, models must have access to extra-sentential linguistic context. There has been recent interest in modelling context in neural machine translation (NMT), but models have been principally evaluated with standard automatic metrics, poorly adapted to evaluating discourse phenomena. In this article, we present hand-crafted, discourse test sets, designed to test the models{'} ability to exploit previous source and target sentences. We investigate the performance of recently proposed multi-encoder NMT models trained on subtitles for English to French. We also explore a novel way of exploiting context from the previous sentence. Despite gains using BLEU, multi-encoder models give limited improvement in the handling of discourse phenomena: 50{\%} accuracy on our coreference test set and 53.5{\%} for coherence/cohesion (compared to a non-contextual baseline of 50{\%}). A simple strategy of decoding the concatenation of the previous and current sentence leads to good performance, and our novel strategy of multi-encoding and decoding of two sentences leads to the best performance (72.5{\%} for coreference and 57{\%} for coherence/cohesion), highlighting the importance of target-side context.
Article
This paper investigates the translation spaces of a very specific translation practice, namely transcreation. In a marketing context, transcreation is usually concerned with the adaptation of advertising material into several different languages or for different markets. The paper is based on an ethnographic field study carried out at a marketing implementation agency in London, during which a group of transcreation managers was followed over a period of four weeks. The study relies mainly on observations of the interactions between the employees of the above-mentioned agency and their partners as well as on the researcher’s own participation in some of the agency’s work-related activities. As an activity, transcreation often involves two or more writers. These writers are most likely to be physically separated, but as the data from this study show, a transcreation agency can serve as a case for joint, situated efforts.
Article
Despite considerable advances in machine translation (MT), adoption by professional translators still meets with resistance. Research on the human factors associated with MT (non-)adoption is required to understand this state of affairs. We investigate whether two specific groups of professional translators use MT, what reasons they advance for its use/non-use and what factors might explain the reasons given. Participants advanced an equally diverse set of reasons for using MT as for not using it, and this was strongly linked to text type, language pair, quality and trust. Using an agency theory lens, we found evidence of Pickering’s dialectics of resistance and accommodation in the focus group data. We also found that one group of translators is more open to the use of MT, and suggest that the socio-technical context of deployment might explain this finding.
Article
Recent decades have brought significant changes in the subtitling industry, both in terms of workflow and in the context of the market for audiovisual translation (AVT). Machine translation (MT), whilst in regular use in the traditional localisation industry, has not seen a significant uptake in the subtitling arena. The SUMAT project, an EU-funded project which ran from 2011 to 2014, had as its aim the building and evaluation of viable MT solutions for the subtitling industry in nine bidirectional language pairs. As part of the project, a year-long large-scale evaluation of the output of the resulting MT engines was carried out by trained subtitlers. This paper reports on the impetus behind the investigation of MT for subtitling, previous work in this field, and discusses some of the results of this evaluation, in particular an attempt to measure the extent of productivity gain or loss for subtitlers using MT as opposed to working in the traditional way. The paper examines opportunities and limitations of MT as a viable option for work of this nature and makes recommendations for the training of subtitle post-editors.
Article
This book offers a timely discussion of translation and social media through the lens of three overarching themes that structure the book: theory, training, and professional practice. The author includes references that cite recent translation and social media industry data, while also drawing on contemporary interdisciplinary research to make the content relevant for a wide-ranging audience: students, professionals and researchers alike. Desjardins provides an analysis of some of the new challenges and questions social media pose for translation, which include, but are not limited to, the translation of hashtags and the relevance of indexing, social media literacy and competency in translator training, translator visibility and remuneration in the ‘like’ economy, tactile modalities in social media branding, and social media monitoring and content translation. Examples from a variety of online social media platforms are provided, including Facebook, Twitter, LinkedIn and Instagram. While written primarily from a Translation Studies’ perspective, readers with expertise in Social Media Studies and Communication are also likely to find the content engaging, particularly those interested in intercultural communications and brand management. Renée Desjardins is an Assistant Professor at the University of Saint-Boniface, Canada. Her areas of research include Translation Studies, Canadian Studies, Social Media and Food Studies. She has over ten years of professional translation experience, has worked in social media teams and has taught translation at both the undergraduate and graduate level.
Chapter
Machine translation (MT) is a term used to describe a range of computer-based activities involving translation. This article reviews sixty years of history of MT research and development, concentrating on the essential difficulties and limitations of the task, and how the various approaches have attempted to solve, or more usually work round, these. History of MT is said to date from a period just after the Second World War during which the earliest computers had been used for code-breaking. In the late 1980s the field underwent a major change in direction with the emergence of a radically new way of doing MT. Two main approaches to MT have emerged and these are rulebased and statistics-based. These approaches owe little to conventional linguistic methods and ideas, but it must be recognized that the much faster development cycle has made functional versions of MT systems covering new language pairs become available. © Editorial matter and organization 2011 Kirsten Malmkjær and Kevin Windle. All rights reserved.
Article
This paper examines the collective self-images of Israeli literary translators, assuming that their desired idealized personae are no less effective than their actual performances in regulating the "rules of the game" in their field. In view of translators' popular image of 'invisibility' and 'submissiveness,' my argument is that translators are compelled to make intensive use of self-promotional discourse in their endeavor to establish their profession as a distinctive source of cultural capital. The present analysis is based on around 250 profile articles and interviews, reviews, surveys of translators and other reports in the printed media from the early 1980s through 2004. Three main self-images emerge from this self-presentational discourse: (1) The translator as a custodian of language culture; (2) The translator as an ambassador of foreign cultures and an innovator, and (3) The translator as an artist in his/her own right.
Article
We examine how susceptible jobs are to computerisation. To assess this, we begin by implementing a novel methodology to estimate the probability of computerisation for 702 detailed occupations, using a Gaussian process classifier. Based on these estimates, we examine expected impacts of future computerisation on US labour market outcomes, with the primary objective of analysing the number of jobs at risk and the relationship between an occupations probability of computerisation, wages and educational attainment.
Article
In recent years, machine translation (MT) has begun to take its place alongside translation memory, terminology management and workflow automation as a key tool in large-scale professional translation projects. Nevertheless, misconceptions abound about the ways in which MT affects the professional translation work process. Effective, efficient and appropriate use of MT in professional translation production is a complex affair that requires an awareness and understanding of the factors that shape the success of MT deployments in terms of both systems development and return on investment (ROI). Generally speaking, however, these factors are not well understood by translation buyers, translation agencies or professional translators. This article provides an overview of the factors that shape successful commercial MT use and addresses some common misperceptions surrounding MT in professional translation projects.
Article
The paper proposes a procedure for life estimation of high voltage AC cables in real operating conditions, i.e. subjected to voltage and load cycles, so that electrothermal stress is the dominant aging factor of cable insulation. As possible alternatives for representing the effects of the electrothermal aging of insulation, three life models wellknown in literature are considered, namely the Zurkov, Crine and Arrhenius-IPM models, each within the probabilistic framework needed for associating time-to-failure with reliability. The cumulation of loss-of-life fractions over load cycles is evaluated through Miner's law. The thermal transients that affect insulation as a consequence of cyclic current variations are simulated via the CIGRE two-loop thermal network analog. The procedure is applied to XLPE-insulated high voltage AC cables, subjected to two typical stepwise-constant daily load cycles differing as to the load severity. The application shows that cable life is very sensitive to load cycles, thermal transients and electrothermal synergism, aspects that all deserve attention for estimating accurately the life expectancy of high voltage AC cables in service. The three life models employed, though weighing differently the electrothermal synergism as a consequence of their own functional expressions, give a concordant indication about the possible life extension of cables already in service.
Article
For the state-of-the-art in Machine Translation (MT) to advance, we contend that Statistical MT (SMT) practitioners will have to collaborate with linguists and translators. This has not happened to date for two main reasons: (i) there remain many translators – and even more surprisingly, many experienced MT protagonists – who find the basic model of SMT very difficult to understand; and (ii) while current approaches to MT depend entirely on the availability of large quantities of translated data, very little thought is given to the process by which the data were produced and the kinds of phenomena that are known to exist in real-translated texts. We argue that much light can be shed on these by looking at the areas of contrastive linguistics and translation studies. In this paper, we describe how central linguists and translators are to the MT process, so that SMT developers and researchers may better understand how to include these previously neglected groups in continuing to advance the state-of-the-art. In a companion paper, we describe the workings of SMT in language that is understandable to linguists and translators. If these constituencies are to make an impact in the field of MT, they need to know how their input is used by the SMT systems, and how they can help in the data annotation phase which is crucial if greater strides are to be made than heretofore.
  • T Devezas
Will robots really steal our jobs? An international analysis of the potential long term impact of automation
  • J Hawksworth
  • R Berrinman
“I think it is a wonderful job” On the solidity of the translation profession
  • H V Dam
  • K K Zethsen
  • HV Dam
Translators are not copywriters. Or are they?
  • G Hellmann
New Zealand Society of Translators and Interpreters Annual Conference
  • D Kenny
uTranslated put out of business by machine translation’s ‘sheer convenience
  • G Diño
Koporeto gabanansu hokokushoniokeru kikaihonyakuno kento [Use of MT for Corporate governance reports
  • N Doi
  • M Kondo
  • A Yamafuji
Nyuraru kikaihonyakuno shoyoriyonikansuru ichikosatsu-honyakugaishaniokeru tokkyohonyakudeno jitureshokai [NMT’s commercial use for patent translation at a translation company
  • T Watanabe
  • M Yamamoto
The ethics of machine translation
  • D Kenny
Cats and dogs trigger machine translation row in Canada
  • M Marking