How to form a personalized shortest learning path for vocal skills based on learners’ individual characteristics is the key to improve the efficiency of vocal music teaching. In this paper, on the basis of dynamic key-value memory network, a gating mechanism is used to update students’ knowledge mastery status, and a knowledge tracking model based on dynamic key-value gated recurrent network is proposed to realize the accurate assessment of students’ vocal music level. On this basis, after searching the suboptimal path using the particle swarm algorithm, the shortest path is searched using the ant colony algorithm, which solves the shortcoming of the blindness of the initial search direction of the single ant colony algorithm, and constructs a recommendation model for optimization of the learning path of vocal skills. The results of simulation experiments show that the model AUC and ACC on the ASSIST2015 dataset are 0.7468 and 0.7654, respectively, which are much higher than the highest 0.7281 and 0.7528 in the baseline model. Path optimization was achieved for both ordinary and excellent vocal students, and the average optimization was 4.297 and 3.242 on ASSIST2009, and 3.819 and 3.044 on ASSIST2015.This paper makes an innovative exploration to improve the quality of vocal music teaching.