[LIVE WEBINAR] Analyzing Translation Quality to Help Improve Machine Translation
 

In this webinar we will present the work done by QT21, a European Commission funded research project on machine translation that makes use of translation quality analysis in order to improve machine translation. After an introduction to the different approaches, methods, and tools that are available to analyze quality (manual and/or automated quality estimations, professional translator based or crowd source based) we will:

• summarize their theoretical pros and cons
• describe the data QT21 has generated on 4 language pairs and analyze their value for quality assessment.
• present a way to improve machine translation by incorporating this data within an Automatic Post-Editing system

Presenters 

Prof. Dr. Lucia Speca (University of Sheffield)

Dr. Lucia Specia is Professor of Language Engineering at the Department of Computer Science of the University of Sheffield. Her research focuses on various aspects of data-driven approaches to multilingual language processing, with applications to Machine Translation, Quality Estimation and Text Adaptation. She is the recipient of an ERC Starting Grant on Multimodal Machine Translation (2016-2021) and is involved in other funded research projects on Machine Translation (QT21 21 and CRACKER) and Text Adaptation (SIMPATICO). 

Dr. Marco Turchi (Fondazione Bruno Kessler)

Marco is a researcher in the Human Language Technology Machine Translation (HLT-MT) group at Fondazione Bruno Kessler (FBK) in Trento, Italy. Before joining FBK, he worked as research engineer at the European Commission Joint Research Centre in Italy, at the University of Bristol and at the Xerox Research Centre Europe. He received his Ph.D. degree in Computer Science from the University of Siena, Italy in 2006. 

Dr. Aljoscha Burchardt (DFKI GmbH)

Aljoscha Burchardt is lab manager at the Language Technology Lab of the German Research Center for Artificial Intelligence (DFKI GmbH). His interests include the evaluation of (machine) translation quality and the inclusion of language professionals in the MT R&D workflow. Burchardt is co-developer of the MQM framework for measuring translation quality. He has a background in semantic Language Technology.