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MT Summit XV | Commercial MT Users presentations accepted

by | August 16, 2017

These presentations were accepted for the Commercial MT Users & Translators track:

Farkhat Aminov Yandex.Translate approach to the translation of Turkic languages
Nikhil Bojja Machine Translation in Mobile Games – Augmenting Social Media Text Normalization with Incentivized Feedback
Robin Bonthrone, Konstantin Lakshin Why are we (still) waiting? What premium translators need to use MT effectively.
Fang Cai Productivity Promotion Strategies for Collaborative Translation on Huge-Volume Technical Documents
Dick Csaplar An Advanced Engine for New and Improved MT Results
Jennifer DeCamp Machine Translation and Terminology Management
Alan K. Melby Quality Evaluation of Four Translations of a Kidney Document: focus on reliability
Tomoki Nagase, Tatsuhiro Kudoh, Katsunori Kotani, Wenjun Ye, Takeshi Mori, Yoshiyuki Sakamoto, Nobutoshi Hatanaka, Takamitsu Takeda, Shu Hirata, Hiromi Nakaiwa A Survey of Usage Environment of Machine Translation by Professional Translators
Morgan O’Brien, Ana Duarte Machine Translation for enterprise technical communications – a journey of discovery
Elaine O’Curran MT Quality Evaluations: From Test Environment to Production
Craig Plesco, Nestor Rychtyckyj Enterprise Application of MT: Progress and Challenges
Juan Rowda A Linguist’s Approach to Quality Estimation
Achim Ruopp Industry Shared Metrics with the TAUS Dynamic Quality Dashboard and API
Carla Schelfhout Accurately Predicting Post-editing Time & Labor for Cost-Management
Mark Seligman, Mike Dillinger Adjusting Interaction Levels in a Speech Translation System for Healthcare
Jean Senellart Beyond Text, Machine Translation and NLP for e-discovery
José G. C. de Souza, Marcello Federico MT Quality Estimation for E-Commerce Data
Tanvi Surti User Experience on Skype Translator
Pablo Vazquez & Edith Bendermacher Setting up MT at NetApp – challenges and learnings while implementing MT
Kristina Vulgan Preparing Your Suppliers for Machine Translation
Alex Yanishevsky How Much Cake to Eat: The Case for Targeted MT Engines

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