Reflections on Rhythm Control in the Stage Performance Process of Dancers

Abstract

Abstract The article proposes a dance score generation model based on the graph attention model and Transformer, which first preprocesses the stage motion capture data of dancers, utilizes a multi-scale attention network to realize motion feature aggregation, and introduces the gated loop unit in the Transformer model to enhance the recognition accuracy of dance movements. Based on the recognition of the dancer’s stage movements, the skeleton size normalization is performed on the joints of the dancer’s gestures, and the skeleton replacement method is combined to realize the correction of the dance movements. Next, we test the model’s dance score generation effect, the matching accuracy of dance movements and music rhythm, and evaluate and analyze the quality of dance movement correction. The results show that the Former model in this paper scores 8.33% higher in beat consistency than the traditional dance generation model Bailando, and the matching coefficient of the rhythmic intensity of the generated dance is basically the same as that of the original dance, with a difference of only 0.02-0.06. It shows that the rhythmic control of the stage performance of dancers carried out by the Transformer model can enhance the stage performance power of dancers and strengthen their stage performance. It shows that using the Transformer model to control the rhythm of dancers’ stage performances can improve the stage performance of dancers and enhance the viewability of stage performances.