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Book series image: Machine Translation: Technologies & Applications by Andy Way

Final Volume Concludes Acclaimed Machine Translation Series

Emeritus Professor Andy Way (ADAPT Centre at DCU, and co-founder of ADAPT Research Ireland) has successfully completed the six-volume series he began editing for Springer Nature in 2017, Machine Translation: Technologies & Applications.

The series concludes with the newly published volume, Enhancing LLM Performance: Efficacy, Fine-Tuning, and Inference Techniques, co-edited by Professor Way alongside his former ADAPT PhD student Dr Peyman Passban, and Dr Mehdi Rezagholizadeh of Huawei Noah’s Ark Labs.

Spanning six books, the collection examines the cutting edge of human and machine translation. It begins with the first comprehensive discussion of translation quality assessment, and extends to practical approaches for addressing the complex challenges of training and deploying large language models. Other volumes investigate ethical and legal implications of machine translation, psychological models of language processing, sign language machine translation, and empirical methods for evaluating translation behaviour and quality.

Together, these works provide an invaluable resource for researchers, developers, and industry professionals engaged with the fast-evolving landscape of translation technologies.

Titles in the Series

  • Translation Quality Assessment: From Principles to Practice
     
  • Translation, Brains and the Computer: A Neurolinguistic Solution to Ambiguity and Complexity in Machine Translation
     
  • Explorations in Empirical Translation Process Research
     
  • Towards Responsible Machine Translation: Ethical and Legal Considerations in Machine Translation
     
  • Sign Language Machine Translation
     
  • Enhancing LLM Performance: Efficacy, Fine-Tuning, and Inference Techniques
     

The series has been shaped by a wide network of international scholars, including Andy Way, Joss Moorkens, Sheila Castilho, Federico Gaspari, Stephen Doherty, Bud Scott, Michael Carl, Helena Moniz, Carla Parra Escartín, Lorraine Leeson, Dimitar Shterionov, Peyman Passban, and Mehdi Rezagholizadeh.

Since publication, the volumes have been accessed over 115,000 times on Springer’s platform, underlining their influence and relevance across academia and industry.

Explore the full series on Springer: Machine Translation: Technologies & Applications.