DocumentCode :
166241
Title :
Using the Echo Nest´s automatically extracted music features for a musicological purpose
Author :
Andersen, Jesper Steen
Author_Institution :
R. Sch. of Libr. & Inf. Sci., Univ. of Copenhagen, Copenhagen, Denmark
fYear :
2014
fDate :
26-28 May 2014
Firstpage :
1
Lastpage :
6
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 consideration 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.
Keywords :
application program interfaces; feature extraction; information retrieval; music; Echo Nest API; Echo Nest music intelligence company; automatic music feature extraction; musicologist; Algorithm design and analysis; Correlation; Educational institutions; Manuals; Music; Music information retrieval; Music information retrieval; digital humanities; information science; musicology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cognitive Information Processing (CIP), 2014 4th International Workshop on
Conference_Location :
Copenhagen
Type :
conf
DOI :
10.1109/CIP.2014.6844510
Filename :
6844510
Link To Document :
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