Research on Automatic Generation System of Dance Movements Based on Deep Learning

It is difficult for traditional generation methods to accurately match dance movements and dance music in the automatic generation of dance. This paper introduces the technologies related to deep learning (DL) and proposes a system for automatic dance generation based on DL. The dance generation algorithm is the system’s linchpin. The first step is to extract dance and audio characteristics. Identifying the skeletal data of the dance movement is crucial to the extraction process. This paper employs an enhanced 3D convolutional neural network to determine the dance movement skeleton sequence. In the second step, a generative model capable of generating dance moves that precisely match the dance music is designed. The experimental results demonstrate that the dance movement recognition method proposed in this paper is highly accurate, that the dance generation method is very close to the actual dance movement, that the music matching rate is more accurate, and that the dance generation effect is favorable.