Come to MT Summit XV to see all of these events:
These presentations were accepted for the Commercial MT Users & Translators track:
| Farkhat Aminov |
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Yandex.Translate approach to the translation of Turkic languages |
| Nikhil Bojja |
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Machine Translation in Mobile Games – Augmenting Social Media Text Normalization with Incentivized Feedback |
| Robin Bonthrone, Konstantin Lakshin |
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Why are we (still) waiting? What premium translators need to use MT effectively. |
| Fang Cai |
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Productivity Promotion Strategies for Collaborative Translation on Huge-Volume Technical Documents |
| Dick Csaplar |
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An Advanced Engine for New and Improved MT Results |
| Jennifer DeCamp |
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Machine Translation and Terminology Management |
| Alan K. Melby |
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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 |
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A Survey of Usage Environment of Machine Translation by Professional Translators |
| Morgan O’Brien, Ana Duarte |
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Machine Translation for enterprise technical communications – a journey of discovery |
| Elaine O’Curran |
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MT Quality Evaluations: From Test Environment to Production |
| Craig Plesco, Nestor Rychtyckyj |
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Enterprise Application of MT: Progress and Challenges |
| Juan Rowda |
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A Linguist’s Approach to Quality Estimation |
| Achim Ruopp |
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Industry Shared Metrics with the TAUS Dynamic Quality Dashboard and API |
| Carla Schelfhout |
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Accurately Predicting Post-editing Time & Labor for Cost-Management |
| Mark Seligman, Mike Dillinger |
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Adjusting Interaction Levels in a Speech Translation System for Healthcare |
| Jean Senellart |
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Beyond Text, Machine Translation and NLP for e-discovery |
| José G. C. de Souza, Marcello Federico |
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MT Quality Estimation for E-Commerce Data |
| Tanvi Surti |
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User Experience on Skype Translator |
| Pablo Vazquez & Edith Bendermacher |
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Setting up MT at NetApp – challenges and learnings while implementing MT |
| Kristina Vulgan |
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Preparing Your Suppliers for Machine Translation |
| Alex Yanishevsky |
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How Much Cake to Eat: The Case for Targeted MT Engines |
Friday, October 30
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Morning Session
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| Introduction to Machine Translation — Jay Marciano, Lionbridge |
| Target Audience: Translators and other translation industry professionals |
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This tutorial is for people who are beginning their journey with machine translation and want an overview of what it is, how it works, how it can be used, and whether it can fulfil their needs. No previous knowledge of machine translation is assumed, and all levels of skepticism are welcome. The focus will be on providing background knowledge that will help you get more out of the rest of MT Summit XV and make more informed decisions about how to use or invest in machine translation. Past participants have ranged from translation professionals who want to understand changes in their field to corporate executives who are evaluating technology strategies for their organizations. The main topics for discussion are common questions about MT (What is MT and how does it differ from other translation technologies? How well can machines really translate? What’s the latest and greatest in MT?), the quality of the translations it produces (Why is the output sometimes so bad? How can the quality be improved? Can translation quality be measured objectively?), its application (What is MT good for? Can it improve a translator’s efficiency? What are the implications of this technology for translators?), return on investment (Is “free” MT really free? How much does MT really cost?), and steps to deployment (Which MT system should we use? What do we do next?). You will leave this tutorial with the tools you need to take part in an informed discussion of MT. |
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Bio: Jay Marciano has been the Director of Real-Time Translation Development at Lionbridge Technologies since 2010 and is currently serving on the Board of Directors of AMTA. Prior to joining Lionbridge, he worked for SDL (2001-2010), where he was responsible for the development and refinement of natural language processing software. He has also worked as a product manager and development lead at Transparent Language, where he was on the team that launched FreeTranslation.com in 1999, a lecturer in the English Department at the University of Bonn, Germany, and as an editor at Houghton Mifflin on the staff of the American Heritage Dictionary. |
| Computer Aided Translation: Advances and Challenges — Philipp Koehn, Johns Hopkins |
| Target Audience: MT Researchers & developers |
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Moving beyond post-editing machine translation, a number of recent research efforts have advanced computer aided translation methods that allow for more interactivity, richer information such as confidence scores, and the completed feedback loop of instant adaptation of machine translation models to user translations. |
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This tutorial will explain the main techniques for several aspects of computer aided translation: confidence measures, interactive machine translation (interactive translation prediction), bilingual concordancers, translation option display, online adaptation, eye tracking, logging, and cognitive user models. For each of these, the state of the art and open challenges are presented. |
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The tutorial will also look under the hood of the open source CASMACAT toolkit that is based on MATECAT, and available as a “Home Edition” to be installed on a desktop machine. The target audience of this tutorials are researchers interested in computer aided machine translation and practitioners who want to use or deploy advanced CAT technology. |
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Bio: Philipp Koehn, PhD, Professor, Department of Computer Science, Whiting School of Engineering, Johns Hopkins University |
Afternoon Session
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| Using Microsoft Translator Hub and Collaborative Translator Framework — Chris Wendt |
| Target Audience: Translators and other translation industry professionals |
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This is a hands-on introduction to using a publicly available SMT system and translation environment. We will discuss the concepts using Microsoft Translator Hub and the Microsoft Translator API as examples. Many of the concepts are transferable to other MT systems, but other MT systems will not be discussed in detail. |
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Agenda: Short overview of statistical MT, Overview of the Microsoft Translator web service and API, Probabilistic models and their function, The power of customization, The Translator Hub: Walk through an engine customization, Training data, suitable and unsuitable documents for training, Domains, Test and tuning sets, Collaborative features in the Translator Hub, Collaborative features in the Translator API and web site widget, Continuous retraining, or one-time shots, Deploying your customized system, Using your customized system in applications, TMSs and CMSs, Using your customized system in your own code |
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Bring your problems, questions and issues. We’ll be able to discuss them and come up with a good solution, which will be helpful for the other attendees. OK if you don’t. Best if you can bring a laptop and if you have translation memory or previously translated documents with at least 5000 segments, but no problem if you don’t have one. |
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Bio: Chris Wendt graduated as Diplom-Informatiker from the University of Hamburg, Germany, and subsequently spent a decade on software internationalization for a multitude of Microsoft products, including Windows, Internet Explorer, MSN and Windows Live, bringing these products to market with equal functionality worldwide. Since 2005 he has led the program management team for Microsoft’s Machine Translation development, responsible for Microsoft Translator services, including Bing Translator and Skype Translator, connecting Microsoft’s research activities with its practical use in services and applications. He is based at Microsoft headquarters in Redmond, Washington. |
| Neural Networks in MT — Kyunghyun Cho, NYU |
| Target Audience: MT Researchers & developers |
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Neural machine translation is a new approach to MT, where a single, large neural network is trained to maximize translation performance. This radical departure from existing (phrase-based) machine translation approaches was proposed independently by several research groups during the last two years (2013-2014). This tutorial will present a detailed description of the two dominant models in neural machine translation; discuss a number of fundamental differences to conventional statistical machine translation; cover a series of recent improvements that have made neural machine translation competitive against phrase-based statistical machine translation; and present future directions of neural machine translation. |
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Bio: Kyunghyun Cho is an assistant professor in the Department of Computer Science, Courant Institute of Mathematical Sciences and the Center for Data Science at New York University (NYU) from September, 2015. Previously, he was a postdoctoral researcher at the University of Montreal under the supervision of Prof. Yoshua Bengio after obtaining a doctorate degree at Aalto University (Finland) in early 2014 under the supervision of Prof. Juha Karhunen, Prof. Tapani Raiko and Dr. Alexander Ilin. Kyunghyun’s main research interests include neural networks, generative models and their applications, especially, to natural language understanding. |
Tuesday, Nov. 3
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Afternoon Session
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| Beyond Post-editing: Interactive and Adaptive Translation Technologies — Spence Green, lilt.com |
| Target Audience: Translators and other translation industry professionals; MT developers |
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Post-editing is an increasingly common mode of machine-assisted translation. Case studies in both academia and industry have recently shown that machine translations can reduce translation time and effort for some domains and language pairs. However, there are two reasons to look beyond current implementations of post-editing. First, the commercial systems most commonly used—Google Translate and Microsoft Translator—are tuned for coverage rather than specific localization settings. Second, it has been known since the 1960s that post-editing is a poor user experience. |
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Interactive and adaptive translation tools were conceived decades ago to address these shortcomings. Until recently, implementations of these ideas were not widely available outside of the research community. This tutorial will introduce tools and techniques that augment the human translator, offering the potential for significant productivity improvements. The material will be accessible to both translation professionals and those interested in new translation technology. There will be four parts: (1) The history of and motivation for interactive translation techniques, (2) the translator’s workflow and where machine intervention can be effective, (3) interactive and adaptive translation technology, (4) practicum: introduction to some tools. |
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Bio: Spence Green recently completed a PhD in computer science at Stanford University supervised by Chris Manning. He was given a Best Paper award at CHI 2013 for his work on mixed-initiative translation. He holds an MS in computer science from Stanford and a BS in computer engineering from the University of Virginia. Currently he is a co-founder of Lilt, a provider of interactive translation systems. |
Precision Translation Tools announces the release of Slate, the first packaged SMT toolkit for native Windows x86-64 operating systems.
Note: “native” means without Cygwin. There is also a parallel Slate package for Linux. Packages include command-line utilities from Moses, MGIZA++ and PTTools necessary to train, tune and evaluate phrase and phrase-factored SMT models. You can find detailed specs about the packages, where to get them at this URL and the “More about Slate for Windows” link at the bottom of the page:
http://www.precisiontranslationtools.com/slate/
http://www.precisiontranslationtools.com/downloads/slate-version-1-0-for-windows/
October 28:
— Introduction to MT (Jay Marciano)
November 1:
— ModernMT (Marcello Federico and Marco Trombetti)
Scroll down for more information.
Introduction to MT October 28, Morning
This tutorial is for people who are beginning their journey with machine translation and want an overview of what it is, how it works, how it can be used, and whether it can fulfil their needs. No previous knowledge of machine translation is assumed, and all levels of skepticism are welcome. The focus will be on providing background knowledge that will help you get more out of the rest of the AMTA conference and make more informed decisions about how to use or invest in machine translation. Past participants have ranged from translation professionals who want to understand changes in their field to corporate executives who are evaluating technology strategies for their organizations. The main topics for discussion are common questions about MT (What is MT and how does it differ from other translation technologies? How well can machines really translate? What are the latest trends in MT research and development?), the quality of the translations it produces (Why is the output sometimes so bad? How can the quality be improved? Can translation quality be measured objectively?), and its application (What is MT good for? Have we reached the point of Star Trek’s universal translator? Will we? Can MT improve a translator’s efficiency? What are the implications of this technology for translators?). You will leave this tutorial with the tools you need to take part in an informed discussion of MT.
Presenter: Jay Marciano
Dependency-Based Statistical Machine Translation October 28, Afternoon
Syntax-based translation models learn translation patterns from recursive structures over sentences. Compared to phrase-based models (Koehn et al., 2003) they have a better capability of long-distance reordering and generalization, especially for MT between distant languages. Constituent structures have been widely used in statistical machine translation (SMT), but translation models built on constituent structures are computationally complex and inefficient when multi-level rules are taken into consideration. By contrast, dependency structures do not attract enough attention in SMT, although dependency grammar is regarded to be very helpful because it directly encodes semantic information and has the best inter-lingual phrasal cohesion properties (Fox, 2002).
In this tutorial, we will introduce representative work on dependency-based SMT, including:
- — Translation models based on segmentation:
o Dependency treelet models
o Dependency graph segmentation models
- — Translation models based on synchronous grammars:
o String-to-dependency models
o Dependency-to-string models
o Dependency-graph-to-string models
- — Dependency-based evaluation
- — Lab session with our open source tools
Presenters: Qun Liu and Liangyou Li
Computer Aided Translation: Advances and Challenges November 1, Morning
Moving beyond post-editing machine translation, a number of recent research efforts have advanced computer aided translation methods that allow for more interactivity, richer information such as confidence scores, and the completed feedback loop of instant adaptation of machine translation models to user translations. This tutorial will explain the main techniques for several aspects of computer aided translation:
– confidence measures
– interactive machine translation (interactive translation prediction)
– bilingual concordancers
– translation option display
– online adaptation
– eye tracking, logging, and cognitive user models
For each of these, the state of the art and open challenges are presented.
The tutorial will also look under the hood of the open source CASMACAT toolkit that is based on MATECAT, and available as a “Home Edition” to be installed on a desktop machine. The target audience of this tutorial are researchers interested in computer aided machine translation and practitioners who want to use or deploy advanced CAT technology.
Presenter: Philipp Koehn
Advances in Neural Machine Translation November 1, Afternoon
Neural machine translation has been introduced to the field of natural language processing and machine translation. Unlike existing approaches to machine translation, neural machine translation tackles the problem of translation by directly modelling the conditional probability of a translation given a source sentence without any assumption on factorization. Already in two years, neural machine translation has proven itself to be competitive against the existing translation approaches in many language pairs, which has excited many researchers in the field. In the first part of this tutorial, I will give an introduction to neural machine translation together with basics in connectionist natural language processing. This will be followed by describing new opportunities in machine translation that have become possible by introducing deep learning to machine translation. These opportunities include sub-word/character-level translation, multilingual translation and simultaneous machine translation.
Presenters: Rico Sennrich, Alexandra Birch, and Marcin Junczys-Dowmunt
ModernMT November 1, Afternoon
The ModernMT project aims at making a contribution to the evolution of machine translation. Our goal is to consolidate the current state of the art technology into a single easy-to-use product, evolving it and keeping it open to integrate the next greatest opportunities in machine intelligence, like deep learning.
In particular, we will introduce and demonstrate the ModernMT system architecture, whose distinguishing features make it particularly useful to be integrated in the Computer-Assisted Translation framework, namely its capability to (i) adapt in real time to the document to be translated and (ii) quickly learn from data provided by the users, such as translation memories and post-edited data. The MMT architecture builds on open source software (Moses, Lucene, etc.) and comes as a-ready-to-install application, that does not require any initial training phase and that enables scalability of data and users.
Our tutorial will cover the following aspects of the ModernMT project:
- — Introduction: main features and development roadmap
- — Development: software architecture and components
- — Field testing: ongoing testing activities with the industry and results
- — Integration: deployment and integration of ModernMT in CAT tools
- — Hands on session: participants will learn how to install, start, and use ModernMT
Presenters: Marcello Federico and Marco Trombetti
MT Summit XV is seeking proposals for tutorials on all topics related to MT. We are interested in tutorials from experts in the following areas:
- MT Researchers and developers
- Commercial MT Users
- Government MT Users, and
- Translators using MT
However, any themes connected to MT research, development, deployment, use, and evaluation are welcome.
Tutorials will be held on Friday, 30 October 2015, immediately preceding the main conference, or Tuesday, 3 November 2015, immediately following the main conference.
Aims
Tutorials at the MT Summit are a forum for experts in MT and MT-related areas to deliver concentrated training on a topic of interest in half-day (or occasionally full-day) teaching sessions. Tutorials provide background that helps conference participants (especially newcomers to the field) understand the conference program, and/or enrich their understanding of particular technical, applied, and business matters surrounding research, development and use of MT and translation technology. Tutorials are often delivered as presentations, sometimes with demos, online information, participant exercises and other instructional materials and activities.
Compensation
The tutorial presenter will receive an honorarium of $500 if there are at least 12 registered attendees for the tutorial. The honorarium will not increase if there is more than one presenter. Please note that for cost reasons, the MT Summit XV organizing committee reserves the right, at its discretion, to cancel any tutorial that has fewer than 8 to 10 registered attendees.
Tutorial materials
The tutorial fees reflect the fact that participants are getting access to an expert, and gaining something of value. It is important to provide well-organized handouts and other materials for the participants. Tutorial speakers are responsible for providing materials such as presentation slides, and other materials that form part of the tutorial (all in PDF format) to AMTA so that tutorial registrants can access the materials online before the tutorial session and if they wish, to print them out and bring it along with them to AMTA 2014. Tutorial speakers have to provide these materials to the Tutorials chair on or before the tutorial materials due date.
How to submit a tutorial proposal
Visit the following link to submit your proposal: MT_Summit_XV_Tutorial_Proposal_Form
After you have submitted your proposal, you can continue to edit your proposal submission until the submission deadline.
If you have any questions about the Tutorials proposal submission process then please contact the MT
Summit XV Tutorials Chair: Jay Marciano (tutorials@amtaweb.org) with the subject line: “MT Summit XV tutorial proposal”.
Important dates:
- Proposal submission deadline (extended): Monday, 29 June 2015
- Notification: Monday, 3 August 2015
- Tutorial materials due date: Monday, 28 September 2015
- Tutorial days: Friday, 30 October 2015 or Tuesday, 3 November 2015
by Darius Hughes | August 16, 2017
Come to MT Summit XV to see all of these events: Schedule-MTSummit2015_oct7 Keynote Speakers Papers in the MT Researchers’ Track Presentations in the Commercial MT Users & Translators’ Track Presentations in the Government MT Users’ Track Tutorials Workshops Technology Showcase Social Program: Banquet at the Rusty Pelican, Sunday November 1 at 6:30 PM
Archieve Read more...
by Darius Hughes | 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. […]
Archieve Read more...
by Darius Hughes | August 16, 2017
Friday, October 30 Morning Session Introduction to Machine Translation — Jay Marciano, Lionbridge Target Audience: Translators and other translation industry professionals This tutorial is for people who are beginning their journey with machine translation and want an overview of what it is, how it works, how it can be used, and whether it can […]
Archieve Read more...
by Darius Hughes | June 24, 2017
Precision Translation Tools announces the release of Slate, the first packaged SMT toolkit for native Windows x86-64 operating systems. Note: “native” means without Cygwin. There is also a parallel Slate package for Linux. Packages include command-line utilities from Moses, MGIZA++ and PTTools necessary to train, tune and evaluate phrase and phrase-factored SMT models. You can […]
Developers Read more...
by Darius Hughes | June 12, 2017
October 28: — Introduction to MT (Jay Marciano) — Dependency-Based Statistical Machine Translation (Qun Liu and Liangyou Li) November 1: — Computer Aided Translation: Advances and Challenges (Philipp Koehn) — Advances in Neural Machine Translation (Rico Sennrich, Alexandra Birch, and Marcin Junczys-Dowmunt) — ModernMT (Marcello Federico and Marco Trombetti) Scroll down for more information. […]
Archieve Read more...
by Darius Hughes | June 12, 2017
Contact: Jay Marciano (tutorials@amtaweb.org) MT Summit XV is seeking proposals for tutorials on all topics related to MT. We are interested in tutorials from experts in the following areas: MT Researchers and developers Commercial MT Users Government MT Users, and Translators using MT However, any themes connected to MT research, development, deployment, use, and evaluation […]
Archieve Read more...