Characteristics of Polyphonic Music Style and Markov Model of Pitch-Class Intervals

  • Eita NakamuraEmail author
  • Shinji Takaki
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9110)


For the purpose of quantitatively characterising polyphonic music styles, we study computational analysis of some traditionally recognised harmonic and melodic features and their statistics. While a direct computational analysis is not easy due to the need for chord and key analysis, a method for statistical analysis is developed based on relations between these features and successions of pitch-class (pc) intervals extracted from polyphonic music data. With these relations, we can explain some patterns seen in the model parameters obtained from classical pieces and reduce a significant number of model parameters (110 to five) without heavy deterioration of accuracies of discriminating composers in and around the common practice period, showing the significance of the features. The method can be applied for polyphonic music style analyses for both typed score data and performed MIDI data, and can possibly improve the state-of-the-art music style classification algorithms.


Polyphonic music analysis Pitch class interval Statistical music model Music style recognition Composer discrimination 



This work is supported in part by Grant-in-Aid for Scientific Research from Japan Society for the Promotion of Science, No. 25880029 (E.N.).


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.National Institute of InformaticsTokyoJapan

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