Advancing Best Practices on Machine Translation Quality Estimation

The translation industry is adopting machine translation (MT) in increasing numbers. Yet a prerequisite for efficient adoption, the evaluation of MT output quality, remains a major challenge for all.

TAUS has worked with its members to develop the Dynamic Quality Evaluation Framework (DQF). The framework allows users to profile their content and receive guidance on the best-fit evaluation techniques. A knowledgebase documenting best practices provides detailed practical information on how to carry out seven specific types of quality evaluation.