This paper integrates the concepts of education and cultivation systems of universities in different ceramic regions, combines the design of interpreting teaching courses with ceramic majors, and designs a blended teaching mode based on spoken corpus to assist the cultivation of ceramic interpreting talents. An audio retrieval algorithm based on ASF features is proposed to accelerate the processing of initial audio. The retrieval algorithm G1-FR for music similarity is selected to enhance retrieval speed and optimize the teaching operation of the ceramic interpreter corpus. Using the interpretation corpus to establish a student-centered online and offline hybrid teaching mode to meet the needs of professional practice-oriented ceramic interpreting talent training. Designing teaching experiments to analyze changes in students’ ceramic interpreting performance. Score the new model of ceramic interpreting talent training based on the interpreting corpus in four dimensions from the students’ perspective. The mean values of students’ evaluation of professional competence, inter-professional competence, methodological competence, and social competence are 3.773, 3.847, 3.810, and 3.905, respectively, all of which are at a medium to high level. And the students value professional and inter-professional abilities in ceramic interpreting more. It shows that the talent cultivation model proposed in this paper has certain feasibility, but it still needs to deepen the students’ career demand and internalize the cultivation of ceramic interpreting professional ability.