Music Expression Understanding Based on a Joint Semantic Space

Authors:
Luca Mion;Giovanni Poli
Affiliations:
Department of Information Engineering, University of Padova, Via Gradenigo 6/a, 35131 Padova, Italy;Department of Information Engineering, University of Padova, Via Gradenigo 6/a, 35131 Padova, Italy
Venue:
AI*IA '07 Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing
Year:
2007

Citing 4
Cited 0

Communicating Expressiveness and Affect in Multimodal Interactive Systems

IEEE MultiMedia
A Direct Method of Nonparametric Measurement Selection

IEEE Transactions on Computers
A Nonlinear Method for Stochastic Spectrum Estimation in the Modeling of Musical Sounds

IEEE Transactions on Audio, Speech, and Language Processing
Automatic mood detection and tracking of music audio signals

IEEE Transactions on Audio, Speech, and Language Processing

Quantified Score

Hi-index	0.00

Visualization

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.