A Professionally Annotated and Enriched Multimodal Data Set on Popular Music

Description

This paper presents the MusiClef data set, a multimodal data set of professionally annotated music. It includes editorial meta-data about songs, albums, and artists, as well as MusicBrainz identifiers to facilitate linking to other data sets. In addition, several audio features (generic low-level descriptors and state-of-the-art music features) are provided. Different sets of annotations as well as music context data – collaboratively generated user tags, web pages about artists and albums, and the annotation labels provided by music experts – are included too. Versions of this data set were used in the MusiCLEF 2011 and in the MusiClef 2012 evaluation campaigns for auto-tagging tasks. In this paper, we report on the motivation for the data set, on its composition, on related sets, and on the evaluation campaigns in which versions of the set were already used. These campaigns likewise represent one use case, i.e. music auto-tagging, of the data set. The complete data set is publicly available for download at http://www.cp.jku.at/musiclef.

Period	01 Mar 2013
Event title	4th ACM Multimedia Systems Conference (MMSys 2013),
Event type	Conference
Location	NorwayShow on map