Musical style identification with n-grams and neural networks

Abstract

Musical Style Identification (MSI) aims to automatically classify music by style. It is being recently explored, mostly in the field of multimedia databases, with potential applications to content-based retrieval. But MSI may be also employed in other applications. We try to face up this challenge with two different methodologies: n-gram Models and Neural Networks. Very good results were obtained with n-grams in our previous research and we were willing to test how other Artificial Intelligence techniques performed with this task, so we began a preliminary study with Multilayer Perceptrons that is promising. © 2008 Springer-Verlag Berlin Heidelberg.