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AMTA 2016 | Accepted Papers and Presentations

MT Researchers Track

Sawsan Alqahtani, Mahmoud Ghoneim and Mona Diab
The Impact of Different Phonological Patterns on Arabic-English Statistical Machine Translation

Rajen Chatterjee, Mihael Arcan, Matteo Negri and Marco Turchi
Instance Selection for Online Automatic Post-Editing in a multi-domain scenario
Boxing Chen, Roland Kuhn, George Foster, Colin Cherry and Fei Huang
Bilingual Methods for Adaptive Training Data Selection for Machine Translation
Wenhu Chen, Evgeny Matusov, Shahram Khadivi and Jan-Thorsten Peter
Guided Alignment Training for Topic-Aware Neural Machine Translation
Hamidreza Ghader and Christof Monz
Which Words Matter in Defining Phrase Reordering Behavior in Statistical Machine Translation?
Biman Gujral, Huda Khayrallah and Philipp Koehn
Translation of Unknown Words in Low Resource Languages
John Hewitt, Matt Post and David Yarowsky
Automatic Construction of Morphologically Motivated Translation Models for Highly Inflected, Low-Resource Languages
Hieu Hoang, Nikolay Bogoychev, Lane Schwartz and Marcin Junczys-Dowmunt
Fast, Scalable Phrase-Based SMT Decoding
Kenji Imamura and Eiichiro Sumita
Multi-domain Adaptation for Statistical Machine Translation Based on Feature Augmentation
Rebecca Knowles and Philipp Koehn
Neural Interactive Translation Prediction
Ander Martinez and Yuji Matsumoto
Improving Neural Machine Translation on resource-limited pairs using auxiliary data of a third language
John Ortega, Felipe Sánchez-Martínez and Mikel Forcada
Fuzzy-match repair using black-box machine translation systems: what can be expected?
Youngki Park, Hwidong Na, Hodong Lee, Jihyun Lee and Inchul Song
An Effective Diverse Decoding Scheme for Robust Synonymous Sentence Translation
Marina Sanchez-Torron and Philipp Koehn
Machine Translation Quality and Post-Editor Productivity
Daniel Torregrosa, Juan Antonio Pérez-Ortiz and Mikel Forcada
Ranking suggestions for black-box interactive translation prediction systems with multilayer perceptrons

Commercial Users Track

Yves Champollion, Wordfast LLC
Machine Translation Acceptance Among Professional Linguists: Are We Nearing the Tipping Point

Marcello Federico, FBK
Machine Translation Adaptation from Translation Memories in ModernMT
Irina Galinskaya
, Yandex
Crowdsource for MT at Yandex
Irina Galinskaya
, Yandex
MT for Uralic Languages – Yandex Approach
Duncan Gillespie
, Etsy
Building a Translation Memory to Improve Machine Translation Coverage and Quality
Nadira Hofmann, Star Group
Seamlessly integrating machine translation into existing translation processes (STAR MT and Transit NXT)
Rihards Kalnins, Tilde
What can we really learn from post-editing?
Maxim Khalilov, Booking.com
Evaluation of machine translation quality in e-commerce environment
Ryan Martin, Intel
Multilingual Search with Machine Translation in the Intel Communities
Hitokazu Matsushita, LDS Church
Enhancing a Production TM-MT Environment Using a Quotation TM
Dragos Munteanu, SDL
Improving Machine Translation for Post-Editing via Real Time Adaptation
Raymond Peng, VMWare
Web App UX Layout Sniffer – Rehearsal for UI Localization
Achim Ruopp, TAUS
The reasonable effectiveness of data – using industry shared, public and web data for domain adaptation
Hassan Sajjad, Qatar Computing Research Institute
An Empirical Study based on Post-editing Effort for English to Arabic Machine Translation
Dag Schmidtke, Microsoft
MT Thresholding: Achieving a defined quality bar with a mix of human and machine translation
Dimitar Shterionov, KantanMT
Divide and Conquer Strategy for Large Data MT
Ivan Smolnikov, SmartCAT
MT Post-editing in a Cloud-based environment
Dimitar Shterionov, et al., KantanMT
Improving KantanMT Training Efficiency with FastAlign
John Tinsley, Iconic
What? Why? How? – Factors that impact the success of commercial MT projects
Chris Wendt, Microsoft
Speech translation user experience in practice
Alex Yanishevsky, Welocalize
I ate too much cake – Now what?

Government MT Users Track

Taylor Cassidy and Clare Voss, US Army Research Laboratory
Toward Temporally-aware MT: Can Information Extraction Help Preserve Temporal Interpretations
Doug Jones, MIT Lincoln Laboratory
Proto-MT Evaluation for Humanitarian Assistance / Disaster Response Scenarios
Lucie Langlois, Michel Simard, Elliott Macklovitch, Courts Administration Service, Government of Canada
Machine Translation of Canadian Court Decisions
Marianna Martindale, U.S. Government
MoJo: Bringing Hybrid MT to CAMT
Mike Maxwell, CASL
Erica Michael, Petra Bradley, Paul McNamee, Matt Post, University of Maryland Center for Advanced Study of Language and Human Language Technology Center of Excellence, Johns Hopkins University
Putting the “human” back in HLT: The importance of human evaluation in assessing the quality and potential uses of translation technology
Jeffrey Micher, US Army Research Laboratory
Machine Translation for a Low-Resource, Polysynthetic Language
Patricia O’Neill-Brown, Ph.D., Nicolas Malyska, U.S. Government, MIT Lincoln Laboratory
Sign Language Translation
Patricia O’Neill-Brown, Ph.D., U.S. Government
Invisible MT
Carl Rubino, IARPA
MATERIAL: IARPA’s Upcoming Machine Translation Program
Michelle Vanni, US Army Research Laboratory
Principle-Based Preparation of Bitext Data

Katherine M. Young, Jeremy Gwinnup, Lane O. Schwartz, N-Space, AFRL, University of Illinois
A Taxonomy of Weeds: A Field Guide for Corpus Curators to Winnowing the Parallel Text Harvest

Panel: Stages of Technology Insertion
Lucie Langlois, Courts Administration Service, Government of Canada

Erica Michael, Petra Bradley, Paul McNamee, Matt Post, University of Maryland Center for Advanced Study of Language and Human Language Technology Center of Excellence, Johns Hopkins University

Danielle Silverman, National Virtual Translation Center