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Record Nr. |
UNINA9910865247603321 |
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Autore |
Peng Yuhong |
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Titolo |
New Advances in Translation Technology : Applications and Pedagogy |
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Pubbl/distr/stampa |
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Singapore : , : Springer Singapore Pte. Limited, , 2024 |
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©2024 |
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ISBN |
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9789819729586 |
9789819729579 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (281 pages) |
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Collana |
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New Frontiers in Translation Studies |
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Altri autori (Persone) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Intro -- Contents -- Introduction: Charting the Future of Translation Technology -- References -- Rise and Application of Translation Technology -- The Rise of Translation Technology and Its Historical and Continued Symbiotic Relationship to the Pursuit of Ideological Power -- 1 Introduction -- 2 Translation Technology's Absence in Translation Studies -- 3 Making Sense of Translation Technology -- 4 The Main Architects of the First Western MT Developments -- 5 The Assumptions Underlying the Drive Towards Fully Automated High-Quality Translation (FAHQT) -- 6 The Ideological Significance of Language Choice -- 7 'We Transmit Thoughts by Means of Speech': The Georgetown Experiment -- 8 Benefits of the Georgetown Experiment -- 9 Assessing the Viability of the Georgetown Experiment's Claims -- 10 Repercussions of the Georgetown Experiment's Claims -- 11 Was the First MT Endeavours Really a Failure? -- 12 Translation Technology Post9/11 -- 13 Conclusion -- References -- Revolutionising Translation with AI: Unravelling Neural Machine Translation and Generative Pre-trained Large Language Models -- 1 Introduction -- 2 An Overview of Deep Learning -- 2.1 Model Design -- 2.2 Data Collection -- 2.3 Model Training -- 2.4 Model Evaluation -- 3 The Transformer Model Explained -- 3.1 Input and Output of the Transformer Model -- 3.2 Key Components |
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of the Transformer Model -- 3.3 Variants of the Transformer Model -- 4 AI for Translation: NMT and Generative Pre-trained LLMs -- 4.1 NMT -- 4.2 Generative Pre-trained LLMs -- 5 Strengths and Limitations of NMT and LLMs -- 5.1 Strengths -- 5.2 Limitations -- 6 Recommendations for Translation Educators -- 6.1 Focus on Reviewing and Editing Translations -- 6.2 Focus on Specialised Translation Domains and Creative Forms of Translation -- 6.3 Provide In-Depth Exploration of AI-Based Translation Technologies. |
6.4 Enhance Programming and Computational Skills -- 6.5 Design More Sophisticated Assessment Tasks -- 7 Recommendations for Developers -- 7.1 Enhance Domain-Specific and Multilingual Support for Models -- 7.2 Improve Integration of NMT, LLMs, and Other Tools -- 7.3 Develop AI for Cross-Modal Translation -- 7.4 Improve Interpretability and User Interaction -- 8 Concluding Remarks -- References -- Cloud Technologies in Media Localisation (Subtitling and Revoicing) -- 1 Introduction -- 2 Cloud Technologies in the Translation Industry -- 2.1 Cloud Systems -- 2.2 Professional Translation Workbenches -- 2.3 Professional Media Localisation Workstations -- 3 Embedding Cloud Technologies in Media Localisation Practices -- 3.1 Cloud Subtitling -- 3.2 Cloud Revoicing -- 4 Conclusions -- References -- Integrating ASR and MT Tools into Cloud Subtitling Workflows: The ¡Sub! and ¡Sub!2 Projects -- 1 Introduction -- 2 Automation in Subtitling: A Brief Overview -- 3 The ¡Sub! and ¡Sub!2 Projects: Experimental Design -- 4 Results -- 5 Discussion and Conclusions -- References -- Industry Insights About Translation Technologies: Current Needs and Future Trends -- 1 Introduction -- 2 Research Approach -- 2.1 Grey Literature: Market Research and Industry-Related Publications -- 2.2 Sample Selection and Description -- 2.3 Data Analysis and Presentation -- 3 Findings and Discussion -- 3.1 Main Profiles that Require Technology-Related Skills and Know-How -- 3.2 Main Technological Trends -- 4 Final Considerations -- References -- What Kind of Translation Literacy Will Be Automation-Resistant? -- 1 Introduction -- 2 What Do We Know About Automation and Translation Literacy? -- 3 What Do We Know About the Use of Generative AI? -- 4 Methodology: Seeking Answers in an Industry-Derived Database -- 5 Results: Relative Exposure to Automation -- 5.1 Knowledges -- 5.2 Language Skills. |
5.3 Information-Processing Skills -- 5.4 Social Communication Skills -- 5.5 Core Tasks -- 6 Conclusions: Proposals for Translator Training -- 6.1 Teach Languages and Translation Skills as a Basis for Trust -- 6.2 Teach Translation Technologies -- 6.3 Sell Trustworthiness Rather Than Words -- 6.4 Engage in Automation-Related Activities -- 6.5 Emphasize Spoken Communication Skills -- 6.6 Do More Than Translate -- References -- Computational Terminology -- 1 Introduction -- 2 Computational Terminology -- 2.1 Monolingual Terminology Extraction -- 2.2 Multilingual Terminology Extraction -- 2.3 Terminology in Neural Machine Translation -- 2.4 Computational Terminology -- 3 Terminology Tools -- 4 Conclusion -- References -- Pedagogy and Students' Feedback on Translation Technology -- Plain Language in the Age of Neural Machine Translation: An Opportunity for Translators -- 1 Introduction -- 2 Machine Translation -- 2.1 MT and Controlled Language -- 3 Plain Language -- 4 Guidelines for Plain Language and Guidelines for Writing for (Machine) Translation -- 4.1 Guidelines for Preparing Plain Language Summaries for Scholarly Journals -- 4.2 Guidelines for Writing for Translation and Writing for NMT -- 4.3 Comparing the Two Types of Guidelines -- 5 Incorporating Plain Language into Translation Service Offerings -- 6 Incorporating Plain Language Training into Translator Education -- 7 |
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Concluding Remarks -- References -- Acquiring Artificial Intelligence (AI) Terminology in the Specialised Translation Class: A Gamified Strategy -- 1 Introduction -- 2 Creating Gamified Activities for Specialised Translation -- 2.1 Gamification and Game-Like Elements -- 2.2 A Two-Step Protocol -- 3 Testing Students' Performance and Perceptions -- 3.1 Methodology -- 3.2 Participants -- 3.3 Results and Discussion -- 4 Conclusions -- Appendices -- Appendix 1: Pre-task Questionnaire. |
Appendix 2: Post-task Questionnaire -- References -- Things to Do in the Translation Class When Technologies Change: The Case of Generative AI -- 1 How Does Generative AI Affect Translation? -- 2 How Do We Teach Translation Technologies in General? -- 3 Principles for a Pedagogy of Technological Change -- 4 Suggested Activities -- 4.1 Beginners' Mistake: What not to Do -- 4.2 Compare Unaided and Automated -- 4.3 Compare Generative AI Solutions -- 4.4 Compare AI and Machine Translation -- 4.5 Spot the Automation -- 4.6 Compare Generative AI, Neural Machine Translation, and Post-editing -- 4.7 Compare Post-editing with Unaided Translation -- 4.8 Compare Time-On-Task in Post-editing with Unaided Translation -- 4.9 Compare Pre-editing with Unaided Translation -- 4.10 Translate from a Language You don't Know -- 4.11 Check Terminology -- 4.12 Create a Term Base -- 4.13 Play with Prompts -- 4.14 Assess the Risks of Adaptation -- 4.15 Use AI for Summaries or Gist Translation -- 4.16 Use Technologies for Literary Translation -- 4.17 Explain Translation Technologies to Clients -- 4.18 Triage Translations in Different Situations -- 4.19 Speed Trials -- 5 A Conclusion Against Overreaction -- References -- Students' Attitudes Towards Interactive and Adaptive Translation Technology: Four years of Working with Lilt -- 1 Introduction -- 2 Related Research -- 2.1 The Integration of Machine Translation in Translation Technology -- 2.2 From User Interface Needs to User Experience -- 2.3 Translation Technology Teaching and Student Perceptions -- 3 Methodology -- 3.1 Data Collection -- 3.2 Course Content and Student Reports -- 3.3 Data Selection and Coding -- 4 Analysis -- 4.1 Student Attitudes Towards Interactivity and Adaptivity -- 4.2 Positive and Negative Perceptions of Translation Tool Features -- 4.3 Features to Be Added or Improved. |
4.4 Machine Translation Quality -- 5 Discussion -- 5.1 Improving Translation Environments -- 5.2 Improving Translation Technology Teaching -- 6 Conclusion -- References -- Who's afraid of literary post-editing? Performances and Reflections of Student Translators -- 1 Introduction -- 2 Literature Review -- 3 Methods -- 4 Results -- 4.1 Perceptions: For and Against Literary Machine Translation -- 4.2 Are There Any Gains? -- 5 Discussion -- 6 Concluding Remarks -- References. |
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