EAMT 2024
Conference of the European Association of Machine Translation
Location
- Sheffield, England
Links
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
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 2023 will be awarded at the conference, together with a presentation of the winner’s work.