Automatic Musical Genre Classification Using a Flexible Approach
An automated method for classifying music signals into genres is proposed. Up to three genres are assigned to each example along with a measure of the degree of influence. The method is based on a structure formed by taxonomy of four hierarchical layers, with 29 genres in the lowest layer and 10 target genres in the higher layers. In more than 77% of the cases there was successful classification. The computational effort is sufficiently low that this method could be used in real time.
Click to purchase paper or login as an AES member. If your company or school subscribes to the AES Journal then you can look for this paper in the institutional version of the Online Journal. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!
This paper costs $20 for non-members, $5 for AES members and is free for E-Library subscribers.