Tempo Estimation

Tempo estimation, the task of automatically determining the speed of music, aims to improve music information retrieval and human-computer musical interaction. Current research focuses on developing robust and accurate algorithms, often employing deep learning architectures like convolutional and recurrent neural networks, and transformers, to handle diverse musical styles and expressive performances, with a growing emphasis on self-supervised learning to overcome data scarcity. These advancements have implications for applications ranging from music search and recommendation to real-time musical accompaniment systems and the analysis of musical expression.