New advances in translation technology : applications and pedagogy

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Bibliographic Details
Main Authors Peng, Yuhong (Author), Huang, Huihui (Author), Li, Defeng (Author)
Format Electronic eBook
LanguageEnglish
Published Singapore : Springer Singapore Pte. Limited, 2024.
SeriesNew frontiers in translation studies.
Subjects
Online AccessFull text
ISBN9789819729586
9789819729579
Physical Description1 online zdroj (281 stran).

Cover

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245 1 0 |a New advances in translation technology :  |b applications and pedagogy /  |c Yuhong Peng, Huihui Huang, Defeng Li. 
264 1 |a Singapore :  |b Springer Singapore Pte. Limited,  |c 2024. 
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490 1 |a New Frontiers in Translation Studies 
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588 |a Description based upon online resource; title from PDF title page (viewed June 18th, 2024). 
504 |a Obsahuje bibliografické odkazy a index. 
505 0 |a 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) 
505 8 |a 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 
505 8 |a 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 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 
505 8 |a 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 
505 8 |a 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 
500 |a 3 The ¡Sub! and ¡Sub!2 Projects: Experimental Design 
650 0 |a Translating and interpreting. 
650 0 |a Natural language processing (Computer science) 
650 0 |a Computational linguistics. 
650 0 |a Artificial intelligence. 
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700 1 |a Huang, Huihui,  |e author. 
700 1 |a Li, Defeng,  |e author. 
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