Annotation based on DQF-MQM error typology provides a more systematic approach to human evaluation of multilingual content. TAUS as the creator of the DQF-MQM error typology is the right partner to ensure a seamless and effective quality review of your data.
DQF-MQM error typology is one of the most prominent quality evaluation metrics in the industry. It provides a comprehensive catalog of error types, with standardized names and definitions and a mechanism for applying them to analyze translation quality.
DQF-MQM Error Typology is a standard and dynamic model for translation quality evaluation.
Identify errors in text translated by human translators or MT.
Categorize and count translation errors segment-by-segment using commonly used industry criteria for accuracy, language, terminology, style and country standards.
Adapt error categories to suit different content types and (computer-aided) human translation processes.
Partner with us to evaluate your MT output using the DQF-MQM error annotation typology.