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jSymbolic. Jordan Smith – MUMT 611 – 6 March 2008. Overview. jSymbolic extracts high-level features from symbolic (MIDI) data. Walkthrough of the interface Features: Types of features Motivation for choice of features Extraction Planned improvements. Overview.

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jsymbolic

jSymbolic

Jordan Smith – MUMT 611 – 6 March 2008

overview
Overview

jSymbolic extracts high-level features from symbolic (MIDI) data.

  • Walkthrough of the interface
  • Features:
    • Types of features
    • Motivation for choice of features
    • Extraction
  • Planned improvements
overview1
Overview

jSymbolic extracts high-level features from symbolic (MIDI) data.

  • Walkthrough of the interface
  • Features:
    • Types of features
    • Motivation for choice of features
    • Extraction
  • Planned improvements
features
Features
  • 3 kinds of features:
    • Low-level
    • High-level
    • Cultural
features1
Features
  • 7 categories of high-level features:
    • Instrumentation (20)
    • Texture (20)
    • Rhythm (35)
    • Dynamics (4)
    • Pitch statistics (26)
    • Melody (20)
    • Chords (28)
features2
Features
  • Why so many features?
    • Ensure ability to discriminate as many different kinds of music as possible
    • Want features to be as basic as possible, because:
      • They are destined for a machine learning experiment
      • Estimating complex features is controversial
features3
Features
  • Why pick these features?
    • Long history of musicological interest
    • Relative ease of extraction
features4
Features
  • Why pick these features?

“The features described above have been designed according to those used in musicological studies, but there is no theoretical support for their … characterization capability.”

(Ponce de León. 2004. Statistical Description Models for Melody Analysis and Characterization. ICMC Proceedings 149-56.)

slide15
McKay & Fujinaga 2005: Automatic music classification and the importance of instrument identification. Proceedings of the Conference on Interdisciplinary Musicology.
overview2
Overview

jSymbolic extracts high-level features from symbolic (MIDI) data.

  • Walkthrough of the interface
  • Features:
    • Types of features
    • Motivation for choice of features
    • Extraction
  • Planned improvements
using the features
Using the Features
  • Like jAudio, modular features make it easy to add new ones

-- ADDING FEATURES --

Implement a class for the new feature in the jAudioFeatureExtractor/MIDIFeatures directory. It must extend the MIDIFeatureExtractor abstract class.

Add a reference to the new class to the populateFeatureExtractors method in the SymbolicFeatureSelectorPanel class.

  • Features exported to ACE XML or Weka ARFF
feature extraction
Feature Extraction
  • Other than jSymbolic, what is the state of the art in symbolic feature extraction?
  • Borrow from others or invent your own, and implement them by yourself.
  • Use MIDI Toolbox.
midi toolbox vs jsymbolic
MIDI Toolbox vs. jSymbolic
  • jSymbolic

-requires JAVA

-is strictly for extracting features

-analytical goals: usefully and objectively condense information

  • Toolbox

-requires MATLAB

-has tools for manipulating and visualizing data

-analytical goals: estimate a musicologically important feature

planned improvements
Planned Improvements
  • Boost number of features from 111 to 160
  • Ability to operate on non-MIDI symbolic data (MusicXML, GUIDO, kern)
  • Ability to extract over windows
references
References

jSymbolic overview:

  • McKay, C., and I. Fujinaga. 2006. jSymbolic: A feature extractor for MIDI files. Proceedings of the International Computer Music Conference. 302-5.

Details of features implemented in jSymbolic:

  • McKay, C. 2004. Automatic genre classification of MIDI recordings. (M.A. Thesis, McGill University).

Example of jSymbolic’s feature extraction in action:

  • McKay, C., and I. Fujinaga. 2005. Automatic music classification and the importance of instrument identification. Proceedings of the Conference on Interdisciplinary Musicology.

(This study used a previous version of jSymbolic called Bodhidharma.)