Using the Echo Nest's automatically extracted music features for a musicological purpose

Jesper Steen Andersen

doi:10.1109/CIP.2014.6844510

Using the Echo Nest's automatically extracted music features for a musicological purpose

Jesper Steen Andersen^*

^*Corresponding author for this work

1 Citation (Scopus)

Abstract

This paper sums up the preliminary observations and challenges encountered during my first engaging with the music intelligence company Echo Nest's automatically derived data of more than 35 million songs. The overall purpose is to investigate whether musicologists can draw benefit from Echo Nest's API, and to explore what practical and analytical considerations one should take into account when engaging with the numbers derived from the Echo Nest API. This paper suggests that the Echo Nest API hold a large potential of doing new types of analyses and visualizing the results. But it concurrently argues that a careful and critical approach is requisite, when interpreting the results.

Original language	English
Title of host publication	4th International Workshop on Cognitive Information Processing - Proceedings of CIP 2014
Publisher	IEEE Computer Society Press
Publication date	2014
Article number	6844510
ISBN (Print)	9781479936960
DOIs	https://doi.org/10.1109/CIP.2014.6844510
Publication status	Published - 2014
Event	4th International Workshop on Cognitive Information Processing, CIP 2014 - Copenhagen, Denmark Duration: 26 May 2014 → 28 May 2014

Conference

Conference	4th International Workshop on Cognitive Information Processing, CIP 2014
Country/Territory	Denmark
City	Copenhagen
Period	26/05/2014 → 28/05/2014
Sponsor	CoSound, Danish Sound, DTU Compute, IAPR

Keywords

digital humanities
information science
Music information retrieval
musicology

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10.1109/CIP.2014.6844510

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Andersen, JS 2014, Using the Echo Nest's automatically extracted music features for a musicological purpose. in 4th International Workshop on Cognitive Information Processing - Proceedings of CIP 2014., 6844510, IEEE Computer Society Press, 4th International Workshop on Cognitive Information Processing, CIP 2014, Copenhagen, Denmark, 26/05/2014. https://doi.org/10.1109/CIP.2014.6844510

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AB - This paper sums up the preliminary observations and challenges encountered during my first engaging with the music intelligence company Echo Nest's automatically derived data of more than 35 million songs. The overall purpose is to investigate whether musicologists can draw benefit from Echo Nest's API, and to explore what practical and analytical considerations one should take into account when engaging with the numbers derived from the Echo Nest API. This paper suggests that the Echo Nest API hold a large potential of doing new types of analyses and visualizing the results. But it concurrently argues that a careful and critical approach is requisite, when interpreting the results.

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Using the Echo Nest's automatically extracted music features for a musicological purpose

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