Smart and Smarter: AI-enabled Smart LQA for Quality Estimation
We are living in the golden age of artificial intelligence (AI). The technology landscape for digital transformation and its effect on localization is evolving at breakneck speed in large part due to AI advancements. More powerful machines (GPUs), big data and rapidly improving machine learning (ML) algorithms such as transformer models inform strategic global content business decisions. One of the most important fields is quality estimation, which runs the gamut from source content suitability to machine translation confidence scoring (MTCS) to target content suitability. The presentation discusses a framework for global content lifecycle evaluation, focuses production case studies and explains what AI-enabled modules are used to make data-driven business decisions. Key takeaways include:
- Components of the global content lifecycle
- AI-enabled modules for each component of the global content lifecycle
- Data analysis and summary for strategic business decisions
Host organization: Welocalize
Currently the Senior Solutions Architect at Welocalize, Alex Yanishevsky has been in the localization industry for over 15 years in a variety of roles. He has written numerous articles for industry journals and presented at industry conferences. Alex's areas of expertise include machine translation, data mining, computational linguistics and GMS and CAT tools. He earned a Ph.D. in Slavic Literature from Brown University.