Harmonic Navigator: A Gesture-Driven, Corpus-Based Approach to Music Analysis, Composition, and Performance

Authors

  • Bill Manaris College of Charleston
  • David Johnson College of Charleston
  • Yiorgos Vassilandonakis College of Charleston

DOI:

https://doi.org/10.1609/aiide.v9i5.12658

Keywords:

music, harmony, Markov models, genetic algorithms, power-law metrics

Abstract

We present a novel, real-time system for exploring harmonic spaces of musical styles, to generate music in collaboration with human performers utilizing gesture devices (such as the Kinect) together with MIDI and OSC instruments / controllers. This corpus-based environment incorporates statistical and evolutionary components for exploring potential flows through harmonic spaces, utilizing power-law (Zipf-based) metrics for fitness evaluation. It supports visual exploration and navigation of harmonic transition probabilities through interactive gesture control. These probabilities are computed from musical corpora (in MIDI format). Herein we utilize the Classical Music Archives 14,000+ MIDI corpus, among others. The user interface supports real-time exploration of the balance between predictability and surprise for musical composition and performance, and may be used in a variety of musical contexts and applications.

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Published

2021-06-30

How to Cite

Manaris, B., Johnson, D., & Vassilandonakis, Y. (2021). Harmonic Navigator: A Gesture-Driven, Corpus-Based Approach to Music Analysis, Composition, and Performance. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 9(5), 67-74. https://doi.org/10.1609/aiide.v9i5.12658

Issue

Vol. 9 No. 5 (2013): AIIDE Workshop Technical Report WS-13-22 (Musical Metacreation)

Section

Workshop on Musical Metacreation