Unsupervised Accuracy Improvement for Cover Song Detection Using Spectral Connectivity Network.

This paper introduces a new method for improving the accuracy in medium scale music similarity problems. Re- cently, it has been shown that the raw accuracy of query by example systems can be enhanced by considering pri- ors about the distribution of its output or the structure of the music collection being considered. The proposed ap- proach focuses on reducing the dependency to those priors by considering an eigenvalue decomposition of the afore- mentioned system’s output. Experiments carried out in the framework of cover song detection show that the proposed approach has good performance for enhancing a high accu- racy system. Furthermore, it maintains the accuracy level for lower performing systems.