Music Composition

Music composition research increasingly leverages artificial intelligence to generate diverse and high-quality musical pieces, focusing on enhancing user control and creative collaboration. Current approaches utilize various neural network architectures, including recurrent neural networks (RNNs), transformers, and generative adversarial networks (GANs), often incorporating techniques like representation learning and topological data analysis to model musical structures and motifs. This work aims to improve both the aesthetic quality and the expressiveness of algorithmically generated music, impacting fields ranging from music education and entertainment to the broader study of creativity and human-computer interaction.