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Visualising chord progressions in music collections: a big data approach

Kachkaev, A, Wolff, D, Barthet, M, Plumbley, MD, Dykes, J and Weyde, T (2014) Visualising chord progressions in music collections: a big data approach In: 15th International Society for Music Information Retrieval Conference (ISMIR), Taipei, Taiwan, 27-31 Oct 2014 [Late Breaking/Demo paper], 2014-10-27 - 2014-10-31.

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Abstract

The analysis of large datasets of music audio and other representations entails the need for techniques that support musicologists and other users in interpreting extracted data. We explore and develop visualisation techniques of chord sequence patterns mined from a corpus of over one million tracks. The visualisations use different representations of root movements and chord qualities with geometrical representations, and mostly colour mappings for pattern support. The presented visualisations are being developed in close collaboration with musicologists and can help gain insights into the differences of musical genres and styles as well as support the development of new classification methods.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
AuthorsEmailORCID
Kachkaev, AUNSPECIFIEDUNSPECIFIED
Wolff, DUNSPECIFIEDUNSPECIFIED
Barthet, MUNSPECIFIEDUNSPECIFIED
Plumbley, MDUNSPECIFIEDUNSPECIFIED
Dykes, JUNSPECIFIEDUNSPECIFIED
Weyde, TUNSPECIFIEDUNSPECIFIED
Date : October 2014
Related URLs :
Additional Information : Copyright 2014 Alexander Kachkaev, Daniel Wolff, Mathieu Barthet, Mark Plumbley, Jason Dykes, Tillman Weyde. Licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Depositing User : Symplectic Elements
Date Deposited : 22 Apr 2015 14:15
Last Modified : 18 Jun 2015 13:33
URI: http://epubs.surrey.ac.uk/id/eprint/807469

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