@inProceedings{
 id = {e1e258be-9f2f-3888-99f5-7b4f0496fab0},
 title = {Musical Tunes Emotions Identification System by means of Intrinsic Musical Characteristics},
 type = {inProceedings},
 year = {2014},
 keywords = {emotions,intrinsic musical characteristics,music,repetitions},
 created = {2014-12-11T00:03:18.000Z},
 pages = {123-142},
 file_attached = {false},
 profile_id = {1a39a66b-a9cd-3b44-8498-85d3ad34e830},
 group_id = {424eb3e1-9b50-35ed-91d3-65c78c3164d7},
 last_modified = {2014-12-11T05:27:35.000Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Endrjukaite2014},
 abstract = {This paper presents a music-tune analysis system to realize automatic emotion identification and prediction by means of intrinsic musical features. To compute physical elements of music pieces we define three significant tunes parameters. These are: repeated parts or repetitions inside a tune, thumbnail of a music piece, and homogeneity pattern of a tune. Our system consists of music-tune features database and computational mechanism for comparison between different tunes. Based on Hevner’s emotions adjectives groups we created a way of emotion presentation on emotion’s plane with two axes: activity and happiness. That makes it possible to determine perceived emotions of listening to a tune and calculate adjacent emotions on a plane.},
 bibtype = {inProceedings},
 author = {Endrjukaite, Tatiana and Yasushi Kiyoki, undefined},
 booktitle = {24th European Japanese Conference on Information Modelling and Knowledge Bases}
}

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