MT Summit 2021 Accepted Papers
Machine Translation Summit 2021 peer reviews are complete. The Program
committee announces the list of papers accepted. Papers are listed by
track in alphabetical order. Only the presenters are listed here due to
space considerations. Co-authors will be included in the full conference
program schedule.
MT Summit 2021 will take place on August 16-20th as a 5-day virtual
event for MT researchers, users, government experts and all peers in the
profession. Event website: http://mt-summit.com/
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GOVERNMENT TRACK
G1. Neural Translator Designed to Protect the Eastern Border of the
European Union
Artur Nowakowski
Adam Mickiewicz University
G2. Corpus Creation and Evaluation for Speech-to-Text and Speech
Translation
Corey Miller
National Virtual Translation Center
G3. Using OpenNMT on Android devices with TensorFlow Lite
Gerardo Cervantes
U.S. Army Research Laboratory
G4. Dragonfly: Improving Automated Sign Language Recognition (ASLR) with
Synthetic Data
Patricia O'Neill-Brown
U.S. Government
USER TRACK
U1. Deploying MT Quality Estimation on a large scale: Lessons learned
and open questions
Aleš Tamchyna
Memsource
U2. Bad to the Bone: Predicting the Impact of Source on MT
Alex Yanishevsky
Welocalize
U3. Machine Translation Post-Editing (MTPE) from the Perspective of
Translation Trainees: Implications for Translation Pedagogy
Dominika Cholewska
University of Białystok
U4. Lab vs. Production: Two Approaches to Productivity Evaluation for
MTPE for LSPs
Elena Murgolo
Aglatech14
U5. Multi-Domain Adaptation in Neural Machine Translation Through
Multidimensional Tagging
Emmanouil Stergiadis
Booking.com
U6. A Rising Tide Lifts All Boats? Quality Correlation between Human
Translation and Machine Assisted Translation
Evelyn Yang Garland, Ronny Gao
Acta Chinese Language Services
U7. Validating Quality Estimation in a Computer-Aided Translation
Workflow: Speed, Cost and Quality Trade-off
Fernando Alva-Manchego, Sara Szoc, Tom Vanallemeersch
University of Sheffield, Imperial College London, CrossLang
U8. Selecting the best data filtering method for NMT training
Fred Bane, Anna Zaretskaya
Transperfect
U9. Open Source Python implementation of classic hLepor and calibration
of ChLepor on human translation data with Language Agnostic BERT
Sentence Encoding (LABSE) AI model
Gleb Erofeev, Serge Gladkoff, Irina Sorokina
Logrus Global
U10. Accelerated Human NMT Evaluation Approaches for NMT Workflow
Integration
James Phillips
World Intellectual Property Organization
U11. Early-stage development of the SignON application and open
framework - challenges and opportunities
John O'Flaherty
Tilburg University
U12. Field Experiments of Real Time Foreign News Distribution Powered by
MT
Keiji Yasuda
MINDWORD Inc.
U13. Preserving high MT quality for content with inline tags
Konstantin Savenkov
Intento
U14. A Synthesis of Human and Machine: Correlating "New" Automatic
Evaluation Metrics with Human Assessments
Mara Nunziatini, Andrea Alfieri
Welocalize
U15. Neural Translation for European Union (NTEU)
Mercedes García Martínez
Pangeanic
U16. Building MT systems in low resourced languages for Public Sector
users in Croatia, Iceland, Ireland, and Norway
Páraic Sheridan
RWS
U17. MT Human Evaluation - Insights & Approaches
Paula Manzur
Vistatec
U18. Using speech technology in the translation process workflow in
international organizations: A quantitative and qualitative study
Pierrette Bouillon, Jeevanthi Liyanapathirana
University of Geneva
U19. Glossary functionality in commercial MT: does it help? Identifying
best practices for an LSP
Randy Scansani, Loïc Dugast
Acolad
U20. A Data-Centric Approach to Real-World Custom NMT for Arabic
Rebecca Jonsson, Ruba Jaikat
Tarjama
U21. Using Raw MT to make essential information available for a diverse
range of potential customers
Sabine Peng
VMWare
U22. A Review for Large Volumes of Post-edited Data
Silvio Picinini
eBay
U23. From Research to Production: Fine-Grained Analysis of Terminology
Integration
Toms Bergmanis, Mārcis Pinnis, Paula Reichenberg
Tilde, Hieronymus
U24. Data-Driven MT Adoption
Victoria Pratt
RWS
U25. A Common Machine Translation Post-Editing Training Protocol by GALA
Viveta Gen, Lucia Guerrero
GALA MTPE Training Special Interest Group
RESEARCH TRACK
R1. Neural Machine Translation in Low-Resource Setting: a Case Study in
English-Marathi Pair
Aakash Banerjee
Indian Institute of Technology
R2. Sentiment-based Candidate Selection for NMT
Alexander G Jones
Dartmouth College, Boston University
R3. Surprise Language Challenge: Developing a Neural Machine Translation
System between Pashto and English in Two Months
Alexandra Birch
BBC, Deutsche Welle, University of Edinburgh, Universitat d'Alacant,
University of Amsterdam
R4. Introducing Mouse Actions into Interactive-Predictive Neural Machine
Translation
Ángel Navarro
Pattern Recognition and Human Language Technology, Universitat
Politècnica de València
R5. Optimizing Word Alignments with Better Subword Tokenization
Anh Khoa Ngo Ho
Laboratoire Interdisciplinaire des Sciences du Numérique, CNRS
R6. Neural Machine Translation with Inflected Lexicon
Artur Nowakowski
Adam Mickiewicz University
R7. Attainable Text-to-Text Machine Translation vs. Translation: Issues
Beyond Linguistic Processing
Atsushi Fujita
NICT, Japan
R8. Integrating Unsupervised Data Generation into Self-Supervised Neural
Machine Translation for Low-Resource Languages
Dana Ruiter
Saarland University, DFKI
R9. The Effect of Domain and Diacritics in Yoruba-English Neural Machine
Translation
David Adelani
Saarland University, MPI-INF, Masakhane
R10. Sentiment Preservation in Review Translation using Curriculum-based
Reinforcement Framework
Divya Kumari
Indian Institute of Technology, Flipkart
R11. Learning Curricula for Multilingual Neural Machine Translation
Training
Gaurav Kumar
Johns Hopkins University
R12. Investigating Active Learning in Interactive Neural Machine
Translation
Kamal Gupta Indian Institute of Technology Patna
ADAPT Centre
R13. Product Review Translation using Phrase Replacement and
Attention-Guided Noise Augmentation
Kamal Gupta
Indian Institute of Technology, Flipkart
R14. An Alignment-Based Approach to Semi-Supervised Bilingual Lexicon
Induction with Small Parallel Corpora
Kelly V Marchisio
Johns Hopkins University
R15. On nature and causes of observed MT errors
Maja Popovic
ADAPT Centre
R16. Make the Blind Translator See The World: A Novel Transfer Learning
Solution for Multimodal Machine Translation
Minghan Wang
Huawei
R17. Studying The Impact Of Document-level Context On Simultaneous
Neural Machine Translation
Raj Dabre
NICT, CogSmart, Tokyo Institute of Technology
R18. Investigating Softmax Tempering for Training Neural Machine
Translation Models
Raj Dabre, Atsushi Fujita
NICT
R19. Like Chalk and Cheese? On the Effects of Translationese in MT
Training
Rebecca Knowles
National Research Council Canada
R20. Modeling Target-side Inflection in Placeholder Translation
Ryokan Ri
The University of Tokyo
R21. Transformers for Low-Resource Languages: Is Féidir Linn!
Seamus Lankford
Dublin City University, Munster Technological University, ADAPT Centre
R22. A Comparison of Sentence-Weighting Techniques for NMT
Simon Rieß
LMU Munich CIS, SAP SE
R23. Scrambled Translation Problem: A Problem of Denoising UNMT
Tamali Banerjee
Indian Institute of Technology
R24. Crosslingual Embeddings are Essential in UNMT for distant
languages: An English to IndoAryan Case Study
Tamali Banerjee
Indian Institute of Technology
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Event website
http://mt-summit.com/
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