EAMT 2024

Conference of the European Association of Machine Translation


  • Sheffield, England


Important Dates

Deadline for paper submission 08 March
Notification to paper authors 08 April
Camera ready deadline 22 April
Author Registration 08 May
Paper Conference 24 June
Deadline for tutorial submission 08 March
Notification of tutorial acceptance 08 April
Tutorial slides, abstract, bibliography, any other materials 15 May
Tutorial Conference 27 June
Deadline for workshop submission 31 January
Notification for workshop submission 28 February
Workshop Conference 15 May
Deadline for thesis submission 08 February
Award notification 08 March

Call for papers

Categories and topics

Research: technical

  • Deep-learning approaches for machine translation and machine translation evaluation
  • Advances in classical MT paradigms: statistical, rule-based, and hybrid approaches
  • Comparison of various machine translation approaches
  • Technologies for machine translation deployment: quality estimation, domain adaptation, etc.
  • 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, multimodal machine translation, machine translation for user generated content (blogs, social networks), machine translation in computer-aided language learning, etc.
  • Linguistic resources for machine translation: corpora, terminologies, dictionaries, etc.
  • 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, etc.

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, relationship between user profiles and machine translation adoption)
  • Emerging areas for machine translation & post-editing: e.g. audiovisual, game localisation, 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 optimising 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 (e.g. switching between multiple machine translation systems, limiting degradations when updating or upgrading an machine translation system)
  • Implementing open-source machine translation (e.g. strategies to get support, reports on taking pilot results into full deployment, examples of advanced customization sought and obtained thanks to the open-source paradigm, collaboration within open-source machine translation projects)
  • Evaluating machine translation in a real-world setting (e.g. 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 (e.g. enterprise support chat, multilingual content for social media)
  • Machine translation and usability
  • Implementing machine translation to process multilingual content for assimilation purposes (e.g. 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


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


  • 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 2023 will be awarded at the conference, together with a presentation of the winner’s work.

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