@article{
 title = {Extracting emotions from music data},
 type = {article},
 year = {2005},
 identifiers = {[object Object]},
 pages = {456–465},
 websites = {http://www.springerlink.com/index/lrc0995xxl5m12x4.pdf},
 id = {dfac64e2-7276-351c-a675-998f1b50f899},
 created = {2016-11-17T19:13:44.000Z},
 file_attached = {false},
 profile_id = {bca0fddf-79ea-3c29-93ed-6177ce521efd},
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 last_modified = {2017-03-14T16:56:30.626Z},
 tags = {emotions info extraction from music,further reading,musical intelligence: sensing,pdf},
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 abstract = {Music is not only a set of sounds, it evokes emotions, subjectively perceived by listeners. The growing amount of audio data available on CDs and in the Internet wakes up a need for content-based searching through these files. The user may be interested in finding pieces in a specific mood. The goal of this paper is to elaborate tools for such a search. A method for the appropriate objective description (parameterization) of audio files is proposed, and experiments on a set of music pieces are described. The results are summarized in concluding chapter. 1 Introduction Extracting information on emotions from music is difficult for many},
 bibtype = {article},
 author = {Wieczorkowska, Alicja and Synak, Piotr and Lewis, Rory and W. Raś, Z.},
 journal = {Foundations of Intelligent Systems}
}

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