A paradigm for music expression understanding based on a joint semantic space, described by both affective and sensorial adjectives, is presented. Machine learning techniques were employed to select and validate relevant low level features, and an interpretation of the clustered organization based on action and physical analogy is proposed.

Music Expression Understanding Based on a Joint Semantic Space

MION, LUCA;DE POLI, GIOVANNI
2007

Abstract

A paradigm for music expression understanding based on a joint semantic space, described by both affective and sensorial adjectives, is presented. Machine learning techniques were employed to select and validate relevant low level features, and an interpretation of the clustered organization based on action and physical analogy is proposed.
AI*IA 2007: Artificial Intelligence and Human-Oriented Computing
9783540747819
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11577/2436771
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