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Semantic contours in tracks based on emotional tags
pp. 45-66
Abstract
Outlining a high level cognitive approach to how we select media based on affective user preferences, we model the latent semantics of lyrics as patterns of emotional components. Using a selection of affective last.fm tags as top-down emotional buoys, we apply LSA latent semantic analysis to bottom-up represent the correlation of terms and song lyrics in a vector space that reflects the emotional context. Analyzing the resulting patterns of affective components, by comparing them against last.fm tag clouds describing the corresponding songs, we propose that it might be feasible to automatically generate affective user preferences based on song lyrics.
Publication details
Published in:
Jensen Kristoffer (2009) Computer music modeling and retrieval. genesis of meaning in sound and music: 5th international symposium, cmmr 2008 copenhagen, denmark, may 19-23, 2008 revised papers. Dordrecht, Springer.
Pages: 45-66
DOI: 10.1007/978-3-642-02518-1_3
Full citation:
Butkus Andrius (2009) „Semantic contours in tracks based on emotional tags“, In: K. Jensen (ed.), Computer music modeling and retrieval. genesis of meaning in sound and music, Dordrecht, Springer, 45–66.