A book review for translators, linguists and scholars.
What is it about?
This book targets translators, linguists, localizers, and anyone interested in the field (including trainees and scholars). It emphasizes that human expertise remains central. The book equips readers with relevant ML knowledge and skills to communicate effectively with machine learning technologies, addressing users' challenges. This empowers translators to leverage ML's capabilities, improving their competence and efficiency. The book also explores how ML can be used to enhance traditional translator education, prioritizing human learning and integrating machine learning tools.
Why is it important?
Bridges the gap between humans and machines: The field of machine translation (MT) is constantly evolving, but translators still need to interact effectively with these tools. This book equips them with the knowledge to understand and utilize machine learning, improving communication and overcoming possible challenges. Boosting translator competence: By understanding the inner workings of ML and the relevant skills, translators can leverage these tools to their advantage. This can lead to increased efficiency and accuracy and potentially even open doors to new specializations within the field. Adapts education for the future: The book delves into how translator education can adapt to the evolving landscape. By integrating ML into the learning process, translators can be better prepared for the future of their field, where human expertise will continue to be important alongside these powerful tools. This forward-thinking approach instills a sense of preparedness and adaptability in the audience. Prioritizes human expertise: This is a key takeaway. The book doesn't suggest machines will replace translators entirely. Instead, it highlights how humans and machines can work together, with human knowledge and skills remaining central to the translation process.