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| --- | ||
| parent: Events | ||
| title: EAMT 2024 | ||
| description: Conference of the European Association of Machine Translation | ||
| location: Sheffield, England | ||
| name: EAMT 2024 | ||
| startDate: 2024-06-24 | ||
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| seo: | ||
| type: Event | ||
| name: EAMT 2024 | ||
| description: Conference of the European Association of Machine Translation | ||
| startDate: 2024-06-24 | ||
| endDate: 2024-06-27 | ||
| eventAttendanceMode: OfflineEventAttendanceMode | ||
| eventStatus: EventScheduled | ||
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| location: | ||
| type: Place | ||
| name: Sheffield, England | ||
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| organizer: | ||
| type: Organization | ||
| name: European Association of Machine Translation | ||
| url: https://eamt.org | ||
| --- | ||
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| The 25th Annual Conference of the **European Association of Machine Translation 2024** (**[EAMT](/eamt) 2023**) will be hosted in Sheffield, England, from 24 June to 27 June, 2024. | ||
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| EAMT 2024 will be jointly organised by EAMT, ZOO Digital and the University of Sheffield. | ||
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| [eamt2024.sheffield.ac.uk/home](https://eamt2024.sheffield.ac.uk/home) | ||
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| ## Important dates | ||
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| #### Papers | ||
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| | | | | ||
| | --- | --- | | ||
| | Deadline for paper submission | 8 March 2024 | | ||
| | Notification to paper authors | 8 April 2024 | | ||
| | Camera ready deadline | 22 April 2024 | | ||
| | Author Registration | 8 May 2024 | | ||
| | Conference | 24 - 27 June 2024 | | ||
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| #### Tutorials | ||
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| | | | | ||
| | --- | --- | | ||
| | Deadline for tutorial submission | 8 March 2024 | | ||
| | Notification of tutorial acceptance | 8 April 2024 | | ||
| | Tutorial slides, abstract, bibliography, any other materials | 15 May 2024 | | ||
| | Conference | 27 June 2024 | | ||
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| #### Workshops | ||
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| | | | | ||
| | --- | --- | | ||
| | Deadline for workshop submission | 31 January 2024 | | ||
| | Notification for workshop submission | on a rolling basis (no later than 28th February) | | ||
| | Conference | 27 June 2024 | | ||
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| #### Best Thesis Award | ||
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| |. |. | | ||
| | --- | --- | | ||
| | Deadline for thesis submission | 8 February 2024 | | ||
| | Award notification | 8 March 2024 | | ||
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| ## Call for papers | ||
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| ### Categories and topics | ||
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| #### Research: technical | ||
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| - 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. | ||
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| #### Research: translators & users | ||
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| - 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 | ||
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| #### Implementations and case studies | ||
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| - 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 | ||
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| #### Products & Projects | ||
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| **Products** | ||
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| - Tools for machine translation | ||
| - Computer-aided translation | ||
| - Other translation technologies (including commercial products and free/open-source software). | ||
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| **Projects** | ||
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| - Research projects, funded through grants obtained in competitive public or private calls related to machine translation. | ||
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| > 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 | ||
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| > 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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