One of uses of machine translation(MT),is helping readers to read for the gist of a foreign text through a draft transla tion produced by MT engines.Rapid post-editing,as Jeffrey Allen defines it as a"strictly mi...One of uses of machine translation(MT),is helping readers to read for the gist of a foreign text through a draft transla tion produced by MT engines.Rapid post-editing,as Jeffrey Allen defines it as a"strictly minimal editing on texts in order to re move blatant and significant errors without considering stylistic issues",can help present the reader with a roughly comprehensi ble translation as quickly as possible.The purpose of this article is on a proposed set of rapid post-editing guidelines for Biblical Chinese-English MT,with its application on editing the English MT version of Chapter one of Mark(马尔谷福音) of the Chi nese Catholic Bible(天主教思高本圣经) as an example.展开更多
This studyaims to explore the impact of neural machine translation(NMT)postediting on metaphorical expressions from English to Chinese in terms of productivity,translation quality,and the strategies employed.To this e...This studyaims to explore the impact of neural machine translation(NMT)postediting on metaphorical expressions from English to Chinese in terms of productivity,translation quality,and the strategies employed.To this end,a comparative study was carried out with 30 student translators who post-edited or translated a text rich in metaphors.By triangulating datafromkeystroke logging,retrospectiveprotocols,questionnaires,and translation quality evaluation,it was found that:(1)processing metaphorical expressions using NMT post-editing has significantly increased the translators'productivity compared to translating them from scratch;(2)NMT was perceived to be useful in processing metaphorical expressions and post-editing produced fewer errors in the final output than translation from scratch;(3)different strategies were used to process metaphorical expressions in post-editing and from-scratch translation due to the inherent differences in the two tasks,with "direct transfer"used most frequently in post-editing as translators usually rely on the NMT output to produce the final translation but more balanced strategies adopted in from-scratch translation as they need to seek for different solutions to rendering the metaphorical expressions;the quality of NMT output played a major role in what strategies were adopted to process the metaphorical expressions and their final product quality in post-editing,rather than the conventionality of the metaphorical expressions in the source text.Practical and research implications are discussed.展开更多
With the rapid development of artificial intelligence(AI)technologies,including neural machine translation and large language models,the language service industry is undergoing a profound transformation that reshapes ...With the rapid development of artificial intelligence(AI)technologies,including neural machine translation and large language models,the language service industry is undergoing a profound transformation that reshapes both the structure and function of the translation profession.Driven by a“high-efficiency,low-cost”rationale,the traditional role of translators as linguistic mediators is increasingly marginalized,raising concerns about a possible weakening or even“disappearance”of their professional status.Drawing on a systematic review of the evolution of the translation profession and the process of translation industrialization,this study examines the multi-dimensional professional crises precipitated by AI’s impact on translators’labor structures,skill sets,and identity.It further explores potential pathways for professional transformation and value reconstruction in the context of emerging technologies.The findings reveal that translators do not truly“disappear”within AI-driven translation workflows;rather,their professional functions are reconfigured,and their identities redefined.Translators progressively evolve from mere language converters into language service experts,undertaking composite tasks such as text optimization,contextual judgment,cultural adaptation,and terminology management.Against this backdrop,the study proposes a novel competency model for translators in AI-oriented contexts and puts forward multi-dimensional collaborative strategies-including educational reforms,platform-based system enhancements,and the updating of professional certifications-to facilitate a shift from“technical adaptation”to“collaborative leadership”.This research aims to provide both theoretical grounding and practical references for the re-establishment of translator agency,the transformation and upgrading of the language service industry,and the future development of translation education.展开更多
The recent ability of machines to generate text and images that are fluent,coherent,and culturally nuanced is already causing major upheavals in the translation sector.Machine translation tools have exploded in number...The recent ability of machines to generate text and images that are fluent,coherent,and culturally nuanced is already causing major upheavals in the translation sector.Machine translation tools have exploded in number,sophistication,and quality,and the profession of human translator needs to adapt to work within this new environment–and avoid being replaced by it.This paper examines the major changes that have taken place,and which could take place in the near future,and suggests ways of revising translator-training curricula to adapt to these challenges.This is essential at a time when the profession is undergoing profound changes and when all translators and future translators need to be prepared for new skills in the field of post-editing,machine-reading,machine-cultures and multidisciplinarity.After outlining the challenges that AI is causing to the profession and to the norms and values of the translation sector in its current state,the author suggests that translator training should adapt to the new reality of the profession and not to what it used to be.The profession is undergoing profound changes,and all translators and future translators need to find new skills and knowledge in order to continue to work with AI.The article concludes with recommendations on how to design AI-friendly translation programmes that can train students for the post-AI era.展开更多
文摘One of uses of machine translation(MT),is helping readers to read for the gist of a foreign text through a draft transla tion produced by MT engines.Rapid post-editing,as Jeffrey Allen defines it as a"strictly minimal editing on texts in order to re move blatant and significant errors without considering stylistic issues",can help present the reader with a roughly comprehensi ble translation as quickly as possible.The purpose of this article is on a proposed set of rapid post-editing guidelines for Biblical Chinese-English MT,with its application on editing the English MT version of Chapter one of Mark(马尔谷福音) of the Chi nese Catholic Bible(天主教思高本圣经) as an example.
文摘This studyaims to explore the impact of neural machine translation(NMT)postediting on metaphorical expressions from English to Chinese in terms of productivity,translation quality,and the strategies employed.To this end,a comparative study was carried out with 30 student translators who post-edited or translated a text rich in metaphors.By triangulating datafromkeystroke logging,retrospectiveprotocols,questionnaires,and translation quality evaluation,it was found that:(1)processing metaphorical expressions using NMT post-editing has significantly increased the translators'productivity compared to translating them from scratch;(2)NMT was perceived to be useful in processing metaphorical expressions and post-editing produced fewer errors in the final output than translation from scratch;(3)different strategies were used to process metaphorical expressions in post-editing and from-scratch translation due to the inherent differences in the two tasks,with "direct transfer"used most frequently in post-editing as translators usually rely on the NMT output to produce the final translation but more balanced strategies adopted in from-scratch translation as they need to seek for different solutions to rendering the metaphorical expressions;the quality of NMT output played a major role in what strategies were adopted to process the metaphorical expressions and their final product quality in post-editing,rather than the conventionality of the metaphorical expressions in the source text.Practical and research implications are discussed.
文摘With the rapid development of artificial intelligence(AI)technologies,including neural machine translation and large language models,the language service industry is undergoing a profound transformation that reshapes both the structure and function of the translation profession.Driven by a“high-efficiency,low-cost”rationale,the traditional role of translators as linguistic mediators is increasingly marginalized,raising concerns about a possible weakening or even“disappearance”of their professional status.Drawing on a systematic review of the evolution of the translation profession and the process of translation industrialization,this study examines the multi-dimensional professional crises precipitated by AI’s impact on translators’labor structures,skill sets,and identity.It further explores potential pathways for professional transformation and value reconstruction in the context of emerging technologies.The findings reveal that translators do not truly“disappear”within AI-driven translation workflows;rather,their professional functions are reconfigured,and their identities redefined.Translators progressively evolve from mere language converters into language service experts,undertaking composite tasks such as text optimization,contextual judgment,cultural adaptation,and terminology management.Against this backdrop,the study proposes a novel competency model for translators in AI-oriented contexts and puts forward multi-dimensional collaborative strategies-including educational reforms,platform-based system enhancements,and the updating of professional certifications-to facilitate a shift from“technical adaptation”to“collaborative leadership”.This research aims to provide both theoretical grounding and practical references for the re-establishment of translator agency,the transformation and upgrading of the language service industry,and the future development of translation education.
文摘The recent ability of machines to generate text and images that are fluent,coherent,and culturally nuanced is already causing major upheavals in the translation sector.Machine translation tools have exploded in number,sophistication,and quality,and the profession of human translator needs to adapt to work within this new environment–and avoid being replaced by it.This paper examines the major changes that have taken place,and which could take place in the near future,and suggests ways of revising translator-training curricula to adapt to these challenges.This is essential at a time when the profession is undergoing profound changes and when all translators and future translators need to be prepared for new skills in the field of post-editing,machine-reading,machine-cultures and multidisciplinarity.After outlining the challenges that AI is causing to the profession and to the norms and values of the translation sector in its current state,the author suggests that translator training should adapt to the new reality of the profession and not to what it used to be.The profession is undergoing profound changes,and all translators and future translators need to find new skills and knowledge in order to continue to work with AI.The article concludes with recommendations on how to design AI-friendly translation programmes that can train students for the post-AI era.
