Main Conference
Research Track
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Commercial and Government Tracks
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Arianna Bisazza – Leiden University
Research Keynote | Unveiling the Linguistic Weaknesses of Neural MT
Download (4 MB)

Macduff Hughes – Google
Commercial Keynote | Machine Translation Beyond the Sentence
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Carl Rubino – IARPA
Government Keynote | Setting up a Machine Translation Program for IARPA
Download (3 MB)

Glen Poor – Microsoft
Commercial Keynote | Use more Machine Translation and Keep Your Customers Happy
Download (14 MB)


The Role of Authoritative Standards in the MT Environment
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Translation Quality Estimation and Automatic Post-Editing
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Technologies for MT of Low Resource Languages (LoResMT 2018
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De-mystifying Neural MT
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MQM-DQF: A Good Marriage (Translation Quality for the 21st Century)
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Corpora Quality Management for MT – Practices and Role
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In this workshop, we will bring together experts from across the standards community, including from the American Society for Testing and Materials (now just “ASTM International”), the American National Standards Institute (ANSI), the International Organization for Standardization (ISO), the Globalization and Localization Association (GALA), and the World Wide Web Consortium (W3C). These experts will discuss authoritative standards that impact the development, implementation, and evaluation of translation systems and of the interoperability of resources.

The workshop will consist of one-half day of technical presentations with invited talks on topics including the structure of the U.S. and international standards community, developing and implementing standards for translation quality assessment and quality assurance, the Translation API Class and Cases (TAPICC) initiative, and updates to Term Based eXchange (TBX). A panel will discuss gaps in this network of standards. They will also solicit input from co-panelists and from the audience on how to improve the standards and standards processes, particularly in the fast-changing world of semantic and neural technological development. Feedback will be provided to the relevant standards committees.



02:00pm – 02:15pm | Jennifer DeCamp | Introduction
02:15pm – 02:30pm | Jennifer DeCamp | Language Codes
02:30pm – 03:00pm | Sue Ellen Wright | Term Base eXchange (TBX)
03:00pm – 03:30pm | David Filip | XLIFF 2
03:30pm – 04:00pm | Break
04:00pm – 04:30pm | Bill Rivers | Translation Standards
04:30pm – 05:00pm | Arle Lommel | Translation Quality Metrics
05:00pm – 05:30pm | Alan Melby | Translation API Cases and Classes (TAPICC)
05:30pm – 06:00pm | Panel



Jennifer DeCamp

David Filip

Alan Melby

Bill Rivers

Arle Lommel

Sue Ellen Wright



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Nowadays, computer-assisted translation (CAT) tools represent the dominant technology in the translation market – and those including machine translation (MT) engines are on the increase. In this new scenario, where MT and post-editing are becoming the standard portfolio for professional translators, it is of the utmost importance that MT systems are specifically tailored to translators.

In this tutorial, we will present ModernMT, a new open-source MT software whose development was funded by the European Union. ModernMT targets two use cases: enterprises that need dedicated MT services; and professional translators working with CAT tools. This tutorial will focus on both use cases.

In the first part, we will present the ModernMT open source software architecture and guide the audience through its installation on an AWS instance. Then, we demonstrate how to create a new adaptive Neural MT engine from scratch, how to feed its internal memory, and finally how to query it.

In the second part, we will introduce ModernMT’s most distinguishing features when used through a CAT tool: (i) ModernMT does not require any initial training: as soon as translators upload their translation memories in the CAT tool, ModernMT seamlessly and quickly learns from this data; (ii) ModernMT adapts to the content to be translated in real time: the system leverages the training data most similar to the document being translated; (iii) ModernMT learns from user corrections: during the translation workflow, ModernMT constantly learns from the post-edited sentences to improve its translation suggestions. In particular, we will demonstrate ModernMT within MateCat, a popular online professional CAT tool.

In this tutorial, participants will learn about industry trends aiming to develop MT focusing on the specific needs of enterprises and translators. They will see how current state-of-the-art MT technology is being consolidated into a single, easy-to-use product capable of learning from – and evolving through – interaction with users, with the final aim of increasing MT-output utility for the translator in a real professional environment.


Marcello Federico (MMT, FBK) and Davide Caroselli (MMT)

Target Audience:

MT users, specialists, integrators, developers, managers, decision makers.



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In the past three years, the language industry has been converging on the use of the MQM-DQF framework for analytic quality evaluation. It emerged from two separate quality-evaluation approaches: the European Commission-funded Multidimensional Quality Metrics (MQM) and the Dynamic Quality Framework (DQF) from TAUS. Harmonized in 2015, the resulting shared hierarchy of error types allows implementers to classify common translation problems and perform comparative analysis of translation quality.

MQM-DQF is currently undergoing a formal standardization process in ASTM F43 and will remain a free and open framework.

Attendees will learn how to apply MQM-DQF to their particular needs, including use in typical MT research scenarios where it can bring consistency and clarity. They will be better prepared to select a quality assessment methodology that is appropriate to their needs and that can help connect the needs of technology developers, users, linguists, and information consumers.

The tutorial will focus on the following topics:

  1. A typology of translation quality metrics. This discussion will enable participants to understand how MQM-DQF compares to other quality evaluation approaches and the comparative strengths and weaknesses of them.
  2. Overview of MQM-DQF and key features. This detailed overview will highlight how the framework relates to existing standards, the role of translation specifications in evaluating quality, and the approach the specification takes to developing numerical quality scores.
  3. Market adoption. This section will cover the tools that have already adopted MQM/DQF and how they apply it.
  4. Detailed case studies. The presenters will discuss specific use cases submitted by tutorial participants to explore how they can create a customized MQM-DQF metric.
  5. Validity and reliability. This section discusses the importance of determining validity and measuring reliability within a translation quality evaluation system.

Note: The presenters were two of the leads in the harmonization of MQM and DQF and are active in the ongoing standardization effort around the resulting combined approach.


Arle Lommel: (Senior analyst, CSA Research), Alan K. Melby (Chair, LTAC Global)

Target audience:

The target audience includes researchers, developers, and linguists interested in understanding translation quality, ways of assessing it, and the strengths and weaknesses of various approaches.

Does post-editing also require a deep learning curve? How do the neural networks of post-editors work in concert with neural MT engines? Can post-editors and engines be retrained to work more effectively with each other?

In this tutorial, we demystify the process, focus on the latest MT developments and their impact on post-editing practices. We will cover enterprise-scale project integrations, zoom into the nitty- gritty of tool compatibility, address the different use cases of MT and dynamic quality models, and share our insights on BI, how to measure it all for informed stakeholder decisions.



Alex Yanishevsky (Senior Manager, MT and NLP Deployments – Welocalize); Elaine
O’Curran (MT Program Manager – Welocalize)

Target Audience:

This tutorial will provide guidance to translators, LSPs and translation buyers on how to navigate the complex landscape of tools for production, and effectively measure BI and KPIs for MT and post-editing


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Neural Machine Translation technology is progressing at a very rapid pace. In the last few years, the research community has proposed several different architectures with various levels of complexity. However, even complex Neural Networks are really built from simple building blocks; and their functioning is governed by relatively simple rules. In this tutorial, we aim to provide an intuitive understanding of the concepts that lies behind this very successful machine learning paradigm.

In the first part of the tutorial we will explain, through visuals and examples, how Neural Networks work. We will introduce the basic building block, the neuron; illustrate how networks are trained; and discuss the advantages and challenges of deep networks.

The second part will focus on Neural Machine Translation. We will present the main Neural Network architectures that power the current NMT engines: Recurrent Neural Networks with attention, Convolutional Networks for MT, and the Transformer model. We will discuss some of the practical aspects involved in training and deploying high-quality translation engines. Using examples we will illustrate some of the current challenges and limitations of the technology. Last but not least, we will try to look to the future and talk about the still not-fully- realized potential of deep learning.


Dragos Munteanu (Director of Research and Development, Machine Translation – SDL) and Ling Tsou (Research Engineer -SDL)

Target audience:

Localization professionals with limited experience with Neural Networks and Deep Learning


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AMTA 2022 | Announcing the #1 Machine Translation conference as a hybrid event

by Darius Hughes | December 22, 2021

Orlando, Florida, USA 12-16 September AMTA 2022, the premiere Machine Translation conference in 2022, will provide engaging and productive networking opportunities for in-person attendees, as well as virtual access for remote participants from around the world. SUBSCRIBE TO CONFERENCE UPDATES AND TO RECEIVE AN INVITATION The Machine Translation industry is in a fast growth and […]

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MT Summit XVIII 2021 | Proceedings for the Summit, Keynotes and Workshops

by Darius Hughes | October 1, 2021

Main SummitResearch TrackDownload (10.8 MB) Users and Providers TrackDownload (76.2 MB) KeynotesJane Nemcova – AI & ML ExecutiveNatural Language – The Road to infinityDownload (0.2 MB) Graham Neubig – Carnegie Mellon UniversityUnderstanding and Improving Context Usage in Context-aware TranslationDownload (3.7 MB) Lucie Séguin – Translation Bureau of CanadaMachine Translation at the Government of Canada: Reaching […]

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MT Summit XVIII 2021 is now VIRTUAL!

by Darius Hughes | April 24, 2021

Final Call for Papers, Presentations, and Tutorial Proposals The 18th biennial conference of the International Association of Machine Translation 16-20 August 2021 – NOW COMPLETELY VIRTUAL! Due to continuing COVID restrictions on travel, we have decided to hold MT Summit 2021 online on August 16-20, 2021. We have extended the submission deadline for Research papers to Tuesday, May […]

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MT Summit 2021 | 2nd Call for Papers, Presentations, and Workshop and Tutorial Proposals

by Darius Hughes | March 8, 2021

MT Summit XVIII – 2021 The 18th biennial conference of the International Association of Machine Translation 16-20 August 2021, Orlando, Florida, USA We are pleased to distribute the 2nd call for papers and presentations, as well as for proposals for Workshops and Tutorials, for MT Summit XVIII, the 18th Machine Translation Summit, to be held […]

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MT Summit 2021 | 1st Call for Papers, Presentations, and Workshop and Tutorial Proposals

by Darius Hughes | February 7, 2021

MT Summit XVIII – 2021 The 18th biennial conference of the International Association of Machine Translation 16-20 August 2021, Orlando, Florida, USA We are pleased to announce the call for papers and presentations, as well as for proposals for Workshops and Tutorials, for MT Summit XVIII, the 18th Machine Translation Summit, to be held 16-20 […]

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AMTA 2020 | Proceedings for the Conference, Keynotes, Workshops and Tutorials

by Darius Hughes | November 21, 2020

Main ConferenceResearch TrackDownload (6.3 MB)NOTE: The paper entitled “New Approach to Parameter Sharing in Multilingual Neural Machine Translation” has been removed from the Research Track proceedings due to duplication of previous scholarly work, known to the first author, without attribution. Commercial and Government TracksDownload (23.3 MB) KeynotesColin Cherry – Google ResearchResearch Keynote | Research stories […]

AMTA 2020