Vocal Performance

Vocal performance research focuses on understanding and modeling the complexities of the human singing voice, encompassing aspects from acoustic analysis to the synthesis of realistic vocalizations. Current research employs various deep learning architectures, including variational autoencoders, transformers, and convolutional neural networks, to address tasks such as singing voice synthesis, lyrics alignment, singing technique detection, and emotion recognition in music. These advancements have implications for music information retrieval, the creation of realistic synthetic voices, and the development of novel human-computer interaction systems. The field also grapples with challenges like handling diverse vocal styles, background noise, and the creation of large, high-quality datasets for training robust models.