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

Submissions (up to 10 pages, including references) are invited for reports on case studies and implementation experience with MT in small or medium-size businesses in the language industry, as well as implementation scenarios involving large corporations, governments, or NGOs. Contributions are welcome on the following topics:

• Integrating MT and computer-assisted translation into a translation production workflow (e.g. transforming terminology glossaries into MT resources, optimizing translation memory/MT thresholds, mixing online and offline tools, using interactive MT, dealing with MT confidence scores);
• Use of MT to improve translation or localization workflows (e.g. reducing turnaround times, improving translation consistency, increasing the scope of globalization projects);
• Managing change when implementing and using MT (e.g. switching between multiple MT systems, limiting degradations when updating or upgrading an MT system);
• Implementing open-source MT in the SME or enterprise (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 MT projects);
• Evaluating MT in a real-world setting (e.g. error detection strategies employed, metrics used, productivity or translation quality gains achieved);
• Post-editing strategies and tools (e.g. limitations of traditional translation quality assurance tools, challenges associated with post-editing guidelines);
• Legal issues associated with MT, especially MT in the cloud (e.g. copyright, privacy);
• Using MT in social networking or real-time communication (e.g. enterprise support chat, multilingual content for social media);
• Implementing MT to process multilingual content for assimilation purposes (e.g. cross-lingual information retrieval, MT for e-discovery or spam detection, MT for highly dynamic content);
• Implementing MT standards.

Papers should highlight problems and solutions in addition to describing MT integration processes and project settings. Where solutions do not seem to exist, suggestions for MT researchers and developers should be clearly emphasized. For user papers produced by academics, we require co-authorship with the actual users.

Papers should be formatted according to the templates specified below, no longer than 10 pages (including references), and submitted as PDF files to the EasyChair EAMT 2022 page (submission type: EAMT2022 User). Anonymization is not required in the User track submissions.

Please note that 10 pages is the maximum number of pages. Innovative and professional submissions of any length will be evaluated by the committee.

• Tools for machine translation, computer aided translation, and the like (including commercial products and open-source software). The authors should be ready to present the tools in the form of demos or posters during the conference;
• Research projects related to machine translation. The authors should be ready to present the projects in the form of posters during the conference. This follows on from the successful ‘project villages’ held at the last EAMT conferences.

• Measurements of comparative effort (time/keystrokes/cognitive) in translation practices involving MT and their impact on the profession;
• Impact of MT on translators’ work: processes, new invoicing methods (for example, using TER for matching), applicability;
• Psycho-social aspects of MT 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 MT development;
• Freelance translators’ independent use of MT (e.g. for individual productivity and not necessarily a customer requirement);
• MT and usability;
• MT in literary, audiovisual, game localization and creative texts;
• MT and interpreting;
• Ethical and confidentiality issues when using MT;
• MT in various scenarios including health care communication, crisis translation, and climate change;
• MT in the translation/interpreting classroom.