Classification of Music Genres by Means of Listening Tests and Decision Algorithms

  • Aleksandra Dorochowicz
  • Piotr Hoffmann
  • Agata Majdańczuk
  • Bożena Kostek
Part of the Studies in Big Data book series (SBD, volume 40)


The paper compares the results of audio excerpt assignment to a music genre obtained in listening tests and classification by means of decision algorithms. A short review on music description employing music styles and genres is given. Then, assumptions of listening tests to be carried out along with an online survey for assigning audio samples to selected music genres are presented. A framework for music parametrization is created resulting in feature vectors, which are checked for data redundancy. Finally, the effectiveness of the automatic music genre classification employing two decision algorithms is presented. Conclusions contain the results of the comparative analysis of the results obtained in listening tests and automatic genre classification.


Music genre classification Feature extraction Listening tests 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Aleksandra Dorochowicz
    • 1
  • Piotr Hoffmann
    • 1
  • Agata Majdańczuk
    • 1
  • Bożena Kostek
    • 1
  1. 1.Audio Acoustics Laboratory, Faculty of Electronics, Telecommunications and InformaticsGdańsk University of TechnologyGdańskPoland

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