Automatical musical genre detection
Journal Title: Romanian Journal of Human - Computer Interaction - Year 2012, Vol 5, Issue 1
Abstract
This paper describes and applies various methods for automatic computer music segmentation. Based on these results and on the feature extraction techniques used, is tried also a genre classification/recognition of the excerpts used. The algorithms were tested on the Magnatune and MARSYAS datasets, but the implemented software tools can also be used on a variety of sources. The tools described here will be subject to a framework/software system called ADAMS (Advanced Dynamic Analysis of Music Software) that will help evaluate and enhance the various music analysis/composition tasks. This system is based on the MARSYAS open source software framework and contains a module similar to WEKA for data-mining and machine learning tasks.
Authors and Affiliations
Adrian Simion , Ştefan Trăuşan-Matu
Keywords
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