Music Genre Recognition in the Rough Set-Based Environment [chapter]

Piotr Hoffmann, Bożena Kostek
2015 Lecture Notes in Computer Science  
The aim of this paper is to investigate music genre recognition in the rough set-based environment. Experiments involve a parameterized music database containing 1100 music excerpts. The database is divided into 11 classes corresponding to music genres. Tests are conducted using the Rough Set Exploration System (RSES), a toolset for analyzing data with the use of methods based on the rough set theory. Classification effectiveness employing rough sets is compared against k-Nearest Neighbors
more » ... ) and Local Transfer function classifiers (LTF-C). Results obtained are analyzed in terms of global class recognition and also per genre.
doi:10.1007/978-3-319-19941-2_36 fatcat:xgarfliqmbevlmxtcfmuyqheyi