This study constructs a competence framework that covers the most popular interpreting technologies. It adopts an empirical design and uses mainly quantitative methods based on a large-scale survey, comprising 647 questionnaires and 10 interviews. According to the analysis of questionnaire and interview data, the authors identify the main types of interpreting technologies, and the challenges in their application. From the survey data, the authors extracted factors that influence interpreters' technological competence, and found a high probability that these factors (awareness, learning, and skills and knowledge) govern the application of specific technologies. The authors, therefore, put forward a three-dimensional competence framework for interpreting technologies, and investigate their roles and relevance in different aspects of interpreting education, including curriculum design, and teaching and assessment methods.