Ha sido reseñado en:
Translation Quality Assessment: From Principles to Practice
Language Value, ISSN-e 1989-7103, Vol. 13, Vol. 1, 2020, págs. 110-115
This is the first volume that brings together research and practice from academic and industry settings and a combination of human and machine translation evaluation. Its comprehensive collection of papers by leading experts in human and machine translation quality and evaluation who situate current developments and chart future trends fills a clear gap in the literature. This is critical to the successful integration of translation technologies in the industry today, where the lines between human and machine are becoming increasingly blurred by technology: this affects the whole translation landscape, from students and trainers to project managers and professionals, including in-house and freelance translators, as well as, of course, translation scholars and researchers.
The editors have broad experience in translation quality evaluation research, including investigations into professional practice with qualitative and quantitative studies, and the contributors are leading experts in their respective fields, providing a unique set of complementary perspectives on human and machine translation quality and evaluation, combining theoretical and applied approaches.
págs. 1-6
Approaches to Human and Machine Translation Quality Assessment
Sheila Castilho, Stephen Doherty, Federico Gaspari, Joss Moorkens
págs. 9-38
Translation Quality, Quality Management and Agency: Principles and Practice in the European Union Institutions
págs. 39-68
Crowdsourcing and Translation Quality: Novel Approaches in the Language Industry and Translation Studies
págs. 69-93
On Education and Training in Translation Quality Assessment
Stephen Doherty, Joss Moorkens, Federico Gaspari, Sheila Castilho
págs. 95-106
Metrics for Translation Quality Assessment: A Case for Standardising Error Typologies
págs. 109-127
págs. 129-158
págs. 159-178
págs. 179-197
Machine Translation Quality Estimation: Applications and Future Perspectives
págs. 201-235
Machine Translation and Self-post-editing for Academic Writing Support: Quality Explorations
págs. 237-262
págs. 263-287
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