Melodic Models for Polyphonic Music Classification

author: Ruben Hillewaere, Computational Modeling Lab, Vrije Universiteit Brussel
published: Oct. 20, 2009,   recorded: September 2009,   views: 3472
Categories

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

The classification of polyphonic music still presents challenges for current music data mining methods. In this paper we explore the performance of classifiers specifically created for melody on the polyphonic classification task. On a small dataset of string quartet movements of Haydn and Mozart, the melodic n-gram model outperforms the melodic global feature model for composer recognition. Furthermore, a simple model that combines the predictions made from different instrumental parts outperforms models created from any single voice. The results indicate that models taking into account polyphonic information achieve higher classification accuracy.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: