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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  • EP ID EP28884
  • DOI -
  • Views 337
  • Downloads 9

How To Cite

Adrian Simion, Ştefan Trăuşan-Matu (2012). Automatical musical genre detection. Romanian Journal of Human - Computer Interaction, 5(1), -. https://europub.co.uk/articles/-A-28884