Difference between revisions of "AMTA 2020"

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|Homepage=https://amtaweb.org/
 
|Homepage=https://amtaweb.org/
 
|City=Orlando
 
|City=Orlando
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|State=Florida
 
|Country=USA
 
|Country=USA
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|Paper deadline=2020/04/27
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|Notification=2020/06/08
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|Camera ready=2020/07/27
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|Submitting link=https://www.softconf.com/amta2020/papers/
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|has Keynote speaker=Colin Cherry, Mona Diab, Chris Wendt, Eric Paquin
 
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<!-- PLEASE ADAPT OR DELETE THIS PART COMPLETELY - You can just paste in the call for papers and remove this and the last line
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Topics of interest may include, but are not limited to, the following:
  
==Topics==
+
 
==Submissions==
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* Making the business case for adopting MT to drive business requirements, expand markets and engage with customers.
==Important Dates==
+
* Practical applications for using raw (aka stock) MT no human intervention, such as post editing.
 
+
* Novel approaches to using MT in a commercial environment.
==Committees==
+
* Advances in adaptive and interactive MT technologies.
* Co-Organizers
+
* Process and criteria for migrating to Neural MT from other systems, such as Statistical MT.
* General Co-Chairs
+
* Using MT for leveraging between similar languages, such as Simplified and Traditional Chinese, Russian and Ukrainian, Spanish and    Catalan; and language variants such as US to UK English, Brazilian to Continental Portuguese. 
** [[has general chair::some person]], some affiliation, country
+
* MT quality and confidence scoring, tools, and metrics that support business KPIs.
 
+
* Productivity measures and quality frameworks that enhance business processes and translation workflows.
* PC Co-Chairs
+
* TM cleanup and corpus preparation techniques for engine training.
** [[has program chair::some person]], some affiliation, country
+
* Approaches and challenges to building your own MT engines.
 
+
* Quality vs. quantity and fit for purpose when choosing corpora for customizing engines (e.g. Translation Memories, terminology/glossaries, Do Not Translate lists).
* Workshop Chair
+
* MT Post Editing challenges.
** [[has workshop chair::some person]], some affiliation, country
+
* New business applications for MT; for example, speech to speech, speech to text, videos, search and indexing applications, emergency response and disaster management, social media, chatbots.
 
+
* API challenges such as tag handling and/or reordering.
* Panel Chair
+
* Open Standards for machine translation
** [[has OC member::some person]], some affiliation, country
+
* Overview and comparisons of open source MT tools and services.
 
+
* Artificial Intelligence approaches to machine translation including Natural Language Processing or Machine Learning applications to enhance the translation process (e.g. information extraction and retrieval, text categorization, Named Entity Recognition, POS tagging, etc.).
* Seminars Chair
+
* Approaches and challenges to using MT for low-resource or long-tail languages.
** [[has tutorial chair::some person]], some affiliation, country
+
* Advances in domain adaptation.
 
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* Handling potentially offensive, illegal or profane language in MT output
* Demonstration Co-Chairs
 
** [[has demo chair::some person]], some affiliation, country
 
** [[has demo chair::some person]], some affiliation, country
 
 
 
* Local Organizing Co-Chairs
 
** [[has local chair::some person]], some affiliation, country
 
 
 
* Program Committee Members
 
** [[has PC member::some person]], some affiliation, country
 
-->
 

Revision as of 14:57, 9 April 2020

AMTA 2020
14th biennial conference of the Association for Machine Translation in the Americas
Event in series AMTA
Dates 2020/09/08 (iCal) - 2020/09/12
Homepage: https://amtaweb.org/
Submitting link: https://www.softconf.com/amta2020/papers/
Location
Location: Orlando, Florida, USA
Loading map...

Important dates
Papers: 2020/04/27
Submissions: 2020/04/27
Notification: 2020/06/08
Camera ready due: 2020/07/27
Keynote speaker: Colin Cherry, Mona Diab, Chris Wendt, Eric Paquin
Table of Contents


Topics of interest may include, but are not limited to, the following:


* Making the business case for adopting MT to drive business requirements, expand markets and engage with customers.
* Practical applications for using raw (aka stock) MT no human intervention, such as post editing.
* Novel approaches to using MT in a commercial environment.
* Advances in adaptive and interactive MT technologies.
* Process and criteria for migrating to Neural MT from other systems, such as Statistical MT.
* Using MT for leveraging between similar languages, such as Simplified and Traditional Chinese, Russian and Ukrainian, Spanish and     Catalan; and language variants such as US to UK English, Brazilian to Continental Portuguese.  
* MT quality and confidence scoring, tools, and metrics that support business KPIs.
* Productivity measures and quality frameworks that enhance business processes and translation workflows.
* TM cleanup and corpus preparation techniques for engine training.
* Approaches and challenges to building your own MT engines.
* Quality vs. quantity and fit for purpose when choosing corpora for customizing engines (e.g. Translation Memories, terminology/glossaries, Do Not Translate lists).
* MT Post Editing challenges.
* New business applications for MT; for example, speech to speech, speech to text, videos, search and indexing applications, emergency response and disaster management, social media, chatbots.
* API challenges such as tag handling and/or reordering.
* Open Standards for machine translation
* Overview and comparisons of open source MT tools and services.
* Artificial Intelligence approaches to machine translation including Natural Language Processing or Machine Learning applications to enhance the translation process (e.g. information extraction and retrieval, text categorization, Named Entity Recognition, POS tagging, etc.).
* Approaches and challenges to using MT for low-resource or long-tail languages.
* Advances in domain adaptation.
* Handling potentially offensive, illegal or profane language in MT output