Dr Maria Kunilovskaya, University of Wolverhampton
05 November 2021
Title: Human Translation Quality Estimation and Translationese
In the first part of the talk I will present a fairly novel NLP task of human translation quality estimation (HTQE) and discuss problems associated with benchmarking human translation quality. How far do human assessors agree on (human) translation quality? What types of labels/scores can be used to reflect quality? What are the existing approaching to predict these labels? If a professional jury in a translation contest manages to achieve agreement on the top-ranking and, especially on bottom-ranking, translations (with possible fine-grained disagreements about the exact ranks) what does it take to teach a machine to distinguish between good and bad translations? Such a model can be applied in educational and certification contexts for filtering out translations that are definitely below the expected standard to reduce the workload for human assessors. The second part of the talk will explore the concept of translationese, and its potential for learning human translation quality. Do you expect good translations to read smoothly and naturally as if originally-written in the target language? Can we use the distance between translations and the expected target language norm to measure translation quality? I will largely draw on the findings reported in our latest publications:
- Kunilovskaya, M. and G. Corpas Pastor (2021). Translationese and register variation in English-to-Russian professional translation. In L. Lim, D. Li, and V. Wang (Eds.), New Perspectives on Corpus Translation Studies. Springer.
- Kunilovskaya, M., Lapshinova-Koltunski, E., & Mitkov, R. (2021). Translationese in Russian Literary Texts. Proceedings of the 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature. EMNLP.
Maria Kunilovskaya has been engaged in translator education for more than 10 years in her role as an Associate Professor in Contrastive Linguistics and Translation Studies at the University of Tyumen, Russia. Lecturing in Translation Studies, Corpus Linguistics and Text Linguistics, she has also been involved with teaching practical translation classes. She is a strong believer in promoting practical corpus skills that can be immediately applied in everyday activities of a language professional. Her research interests include construction and exploitation of parallel corpora, corpus-based research into translation competence and translationese, most recently with a strong pull towards the computational research methods, especially in the area of human translation quality estimation.