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EAMT 2023

Conference of the European Association of Machine Translation


The 24th Annual Conference of the European Association of Machine Translation 2022 (EAMT 2023) will be hosted in Tampere, Finland, from 12 June to 15 June, 2023.

EAMT 2023 will be jointly organised by EAMT and Tampere University.

events.tuni.fi/eamt23/

Important dates

Papers

   
Deadline for paper submission 3 March 2023
Notification to paper authors 6 April 2023
Author Registration 5 May 2023
Camera ready deadline 5 May 2023
Conference 12 - 15 June 2023

Tutorials

   
Deadline for tutorial submission 3 March 2023
Notification of tutorial acceptance 6 April 2023
Tutorial slides, abstract, bibliography, any other materials 1 June 2023
Conference 12 - 15 June 2023

Workshops

   
Deadline for workshop submission 3 March 2023
Notification for workshop submission on a rolling basis
Conference 12 - 15 June 2023

Keynote speakers

  • Lynne Bowker, Full Professor at the University of Ottawa in Canada
  • Marco Turchi, Head of the Machine Translation activities at Zoom Video Communications
Table of contents
  1. Important dates
    1. Papers
    2. Tutorials
    3. Workshops
  2. Keynote speakers
  3. Call for papers
    1. Categories and topics
      1. Research: technical
      2. Research: translators & users
      3. Implementations and case studies
      4. Products & Projects
      5. Best thesis awards 2023
  4. Call for workshops
  5. Call for tutorials

Call for papers

The European Association for Machine Translation (EAMT) invites everyone interested in machine translation and translation-related tools and resources ― developers, researchers, users, translation and localization professionals and managers ― to participate in this conference.

Categories and topics

Research: technical

  • Deep-learning approaches for machine translation and machine translation evaluation
  • Advances in classical machine translation paradigms: statistical, rule-based, and hybrid approaches
  • Comparison of various machine translation approaches
  • Technologies for machine translation deployment: quality estimation, domain adaptation, and more
  • Resources and evaluation
  • Machine translation in special settings: low resources, massive resources, high volume, low computing resources
  • Machine translation applications: translation/localization aids, speech translation, machine translation for user generated content (blogs, social networks), machine translation in computer-aided language learning, and more
  • Linguistic resources for machine translation: corpora, terminologies, dictionaries, and more
  • Machine translation evaluation techniques, metrics, and evaluation results
  • Human factors in machine translation and user interfaces
  • Related multilingual technologies: natural language generation, information retrieval, text categorization, text summarization, information extraction, optical character recognition, and more

Research: translators & users

  • The impact of machine translation and post-editing: including studies on processes, effort, strategies, usability, productivity, pricing, workflows, and post-editese
  • Human factors and psycho-social aspects of machine translation adoption (ergonomics, motivation, and social impact on the profession)
  • Emerging areas for machine translation and post-editing: audiovisual, game localization, literary texts, creative texts, social media, health care communication, crisis translation
  • Machine translation and ethics
  • The impact of using translators’ metadata and user activity data for monitoring their work
  • The evaluation and reception of different modalities of translation: human translation, post-edited, raw machine translation
  • Machine translation and interpreting
  • Human evaluations of machine translation output
  • Machine translation for gisting and the impact of machine translation on users: use cases, expectations, perceptions, trust, views on acceptability
  • Machine translation and usability
  • Machine translation and education/language learning
  • Machine translation in the translation/interpreting classroom

Implementations and case studies

  • Integrating or optimizing machine translation and computer-assisted translation in translation production workflows (translation memory/machine translation thresholds, mixing online and offline tools, using interactive machine translation, dealing with machine translation confidence scores)
  • Managing change when implementing and using machine translation (for example, switching between multiple machine translation systems, limiting degradations when updating or upgrading an machine translation system)
  • Implementing open-source machine translation (for example, strategies to get support, reports on taking pilot results into full deployment, examples of advanced customisation sought and obtained thanks to the open-source paradigm, collaboration within open-source machine translation projects)
  • Evaluating machine translation in a real-world setting (for example, error detection strategies employed, metrics used, productivity or translation quality gains achieved)
  • Ethical and confidentiality issues when using machine translation, especially machine translation in the cloud
  • Using machine translation in social networking or real-time communication (for example, enterprise support chat, multilingual content for social media)
  • Machine translation and usability
  • Implementing machine translation to process multilingual content for assimilation purposes (for example, cross-lingual information retrieval, machine translation for e-discovery or spam detection, machine translation for highly dynamic content)
  • Machine translation in literary, audiovisual, game localization and creative texts
  • Impact of machine translation and post-editing on translation practices and the profession: processes, effort, compensation
  • Psycho-social aspects of machine translation adoption (ergonomics, motivation, and social impact on the profession)
  • Error analysis and post-editing strategies (including automatic post-editing and automation strategies)
  • The use of translators’ metadata and user activity data in machine translation development
  • Freelance translators’ independent use of machine translation
  • Machine translation and interpreting

Products & Projects

Products

  • Tools for machine translation
  • Computer-aided translation
  • Other translation technologies (including commercial products and free/open-source software).

Projects

  • Research projects, funded through grants obtained in competitive public or private calls related to machine translation.

There will be a poster boaster session for this track, in which authors will have 120 seconds to attract attendees to their posters or demos with a two-slide presentation.

Best thesis awards 2023

The EAMT Best Thesis Award 2023 for PhD theses defended during 2022 will be awarded at the conference, together with a presentation of the winner’s work. Information for candidates for the award will be available soon. Templates for writing your paper

Call for workshops

EAMT workshops are intended to provide the opportunity for MT-related communities of interest to spend focused time together advancing the state of thinking or the state of practice in their area of interest or endeavour. Workshops are generally scheduled as full-day events.

events.tuni.fi/eamt23/call-for-workshop-proposals/

Call for tutorials

The aim of a tutorial is primarily to help the audience to develop understanding of particular technical, applied, and business matters related to research, development, and use of MT and translation technology.

events.tuni.fi/eamt23/call-for-tutorials/


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