Join us for the seventh episode of our Reality Series to dive into the myths and realities of translation quality estimation and assurance as perceived through the lens of the MQM (Multidimensional Quality Metrics) methodology. MQM is a comprehensive system designed to assess and monitor the quality of translated content. MQM serves as a standardized Linguistic Quality Assurance (LQA) framework to evaluate translation quality across various categories. Assessing translations under the MQM framework can help identify strengths in your localization process and opportunities to improve.
In this fireside chat, we'll explore the common mistakes and best practices employed to ensure top-tier linguistic quality. Discover how the MQM methodology can empower localization managers and linguists alike to minimize errors, remove subjectivity and improve their translation output.
Our experts for this session will be:
- Olga Beregovaya | VP of AI and Machine Translation
- Valerie Dehant | Senior Director, Language Services
- Alex Yanishevsky | Director of AI and Machine Translation Deployments
Speakers
Olga Beregovaya
VP, AI & Machine TranslationSmartling
Olga has over 20 years of experience in Language Technology, NLP, Machine Learning, Global Content Transformation and AI Data development and is passionate about growing businesses through driving change and innovation. Olga started her career in language technology building lexicons and rules for Rule-based machine translation, gradually expanding her expertise into other broader applications of NLP and Machine Learning to enterprise translation workflows. Olga has also served as President of AMTA, currently serves as a Vice President and Technology Program Sponsor for Women in Localization and as an Advisor for Engineering Leadership at California State University, Chico. Olga received her MA, Linguistics/Germanic Studies at UC- Berkeley and MA/BA in Linguistics from St. Petersburg State University.
Alex Yanishevsky
Senior Director, AI SolutionsLinkedIn
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