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| Title:
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Emotional nodes among lines of lyrics |
| Type:
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Article in proceedingsArticle in proceedings |
| Participant(s):
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Technical University of Denmark
Email:
Technical University of Denmark
Email:
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| Abstract:
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Recent neuroscience studies have shown that it is
possible to predict how concrete objects are represented in the
brain based on the semantic relations of words defining the
corresponding concepts. Whether we read the word ‘smile’ or
recognize the same expression in a face, the mental processes
captured as event related potentials in EEG brain imaging appear
indistinguishable. As both low-level semantics and our affective
responses can be encoded in words, we propose a simplified
cognitive approach to model how we emotionally perceive media.
Representing song texts in a vector space of reduced
dimensionality using LSA, we define distances between lines of
lyrics and frequently used emotional last.fm tags, that constrain
the latent semantics according to the psychological dimensions of
valence and arousal. We compare the LSA derived emotions from
texts with the user annotated tag clouds describing the
corresponding songs at last.fm, and suggest the retrieved patterns
may provide a sparse representation of how we perceive the
emotional content in media. |
| Published:
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part of: Proceedings of 9th IEEE Conference on automatic face and gesture recognition FG 2011 (ISBN: 978-1-4244-9140-7), pages: 821-826, 2011, IEEE, |
| DOI:
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| Presented at:
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IEEE Conference on automatic face and gesture recognition, Santa Barbara, California, USA |
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