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Finding geographically representative music via social media

Published: 30 November 2011 Publication History

Abstract

People can draw a myriad of semantic associations with music. The semantics can be geographical, ethnographical, society- or time-driven, or simply personal. For certain types of music, however, this semantic association is more prominent and coherent across most peoples. Such music can often serve as an ideal accompaniment for a user activity or setting (that shares the semantics of the music), especially in media authoring applications. Among the strongest associations a piece of music can have is with the geographical area from which it generates. With video-sharing in sites such as YouTube having become a norm, one would expect that music videos tagged with a geographic location keyword are representative of the respective geographical theme. However, in the past few years, the proliferance of western pop culture throughout the world has resulted in popularity of ethnic pop (resembling Western pop) that sounds quite distinct from traditional regional music. While a human expert may easily distinguish between such ethnic pop and traditional regional music, the problem of automatically differentiating between them is still new. The problem becomes more challenging with similarities in music from many different regions. In this paper, we attempt to automatically identify music with strong geographical semantics (that is, "traditional-sounding music" for different geographical regions), using only music gathered from social media sources as our training and testing data. We also explore the use of hierarchical clustering to discover relationships between the music of different cultures, again using only social media.

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Cited By

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  • (2021)Locate your soundscape: interacting with the acoustic environmentMultimedia Tools and Applications10.1007/s11042-021-10683-9Online publication date: 25-Mar-2021
  • (2014)MSVAProceedings of the 22nd ACM international conference on Multimedia10.1145/2647868.2654967(793-796)Online publication date: 3-Nov-2014
  • (2011)1st international ACM workshop on music information retrieval with user-centered and multimodal strategies (MIRUM)Proceedings of the 19th ACM international conference on Multimedia10.1145/2072298.2072386(603-604)Online publication date: 28-Nov-2011

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cover image ACM Conferences
MIRUM '11: Proceedings of the 1st international ACM workshop on Music information retrieval with user-centered and multimodal strategies
November 2011
70 pages
ISBN:9781450309868
DOI:10.1145/2072529
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 30 November 2011

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Author Tags

  1. audio features
  2. crowdsourcing
  3. metric learning
  4. representative music

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MM '11
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MM '11: ACM Multimedia Conference
November 30, 2011
Arizona, Scottsdale, USA

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Cited By

View all
  • (2021)Locate your soundscape: interacting with the acoustic environmentMultimedia Tools and Applications10.1007/s11042-021-10683-9Online publication date: 25-Mar-2021
  • (2014)MSVAProceedings of the 22nd ACM international conference on Multimedia10.1145/2647868.2654967(793-796)Online publication date: 3-Nov-2014
  • (2011)1st international ACM workshop on music information retrieval with user-centered and multimodal strategies (MIRUM)Proceedings of the 19th ACM international conference on Multimedia10.1145/2072298.2072386(603-604)Online publication date: 28-Nov-2011

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