Computational Modelling of Perceptual Music Features
Today, computers and the Internet are commonly used for all aspects of music culture from production to listening. When a typical online music database contains 5 million songs, new computer tools are needed for characterizing, and indexing music audio. This is the focus of the new research field Music Information Retrieval (MIR).
In an earlier project, a new approach was successfully tested using perceptually defined features for describing music in a four-layered approach with audio, low-level features, mid-level perceptual features, and semantic descriptions. A new finding was that these features could be described within a theoretical framework of ecological perception. It also indicated that the computational modeling of the perceptual features was a challenging task.
In the proposed project, we will further expand the feature space using an ecological approach, for example for describing different rhythmical patterns and their relation to motion. A major focus will be the development of computational models for predicting the perceptual features using signal-processing techniques in combination with machine learning methods. Finally, we will develop small proof-of-concept applications in order to disseminate and test the result. A successful result will bridge the semantic gap between earlier studies in music psychology and contemporary data-mining projects leading to new ways of understanding and modeling music audio.
Group: Sound and Music Computing
Anders Friberg (Project leader)
Funding: VR (621-2012-4685)
Duration: 2013 - 2017
Keywords: Music information retrieval, perceptual features, computational models
Journal of the Acoustical Society of America, 141(3), 2224-2242. [abstract] [pdf] (2017). Predicting the perception of performed dynamics in music audio with ensemble learning.
International Computer Music Conference (ICMC), Shanghai, China. [abstract] [pdf] (2017). Cross-cultural aspects of perceptual features in K-Pop: A pilot study comparing Chinese and Swedish listeners. In
Journal of the Acoustical Society of America, 137, 3163-3177. [abstract] [pdf] (2015). Modeling the Perception of Tempo.
PLOS ONE, 10(3), e0119032:1-e0119032:58. [abstract] [pdf] (2015). Idealized computational models for auditory receptive fields.
SSVM 2015: Scale Space and Variational Methods in Computer Vision, Lège Cap Ferret, France, Volume: Springer LNCS 9087 (pp. 3-15). [abstract] [pdf] (2015). Scale-space theory for auditory signals. In
Proceedings of the 40th International Computer Music Conference, ICMC 2014 and 11th Sound and Music Computing Conference, SMC 2014 (pp. 1172-1177). [abstract] [pdf] (2014). Estimation of vocal duration in monaural mixtures. In
Journal of the Acoustical Society of America, 136(4), 1951-1963. [abstract] [pdf] (2014). Using listener-based perceptual features as intermediate representations in music information retrieval.
arXiv:1403.7923 [cs.IR]. [abstract] [link] (2014). Using perceptually defined music features in music information retrieval.
arXiv:1404.2037 [cs.SD]. [abstract] [link] (2014). Idealized computational models for auditory receptive fields.
Proceedings of the Sound and Music Computing Conference (SMC) 2013, Stockholm, Sweden (pp. 19-26). [abstract] [pdf] (2013). A social network integrated game experiment to relate tapping to speed perception and explore rhythm reproduction. In
Frontiers in Psychology, 4(487), 1-12. [abstract] [pdf] (2013). Emotional expression in music: contribution, linearity, and additivity of primary musical cues.
Proceedings of the Sound and Music Computing Conference 2013, SMC 2013, Stockholm, Sweden (pp. 735-741). [abstract] [pdf] (2013). Modelling Perception of Speed in Music Audio. In
Proceedings of the International Symposium on Music Information Retrieval. [abstract] [pdf] (2013). Modelling the Speed of Music Using Features from Harmonic/Percussive Separated Audio. In
Journal of Neuroscience, 33(14), 6070-6080. [abstract] (2013). Experience-Dependent Modulation of Feedback Integration during Singing: Role of the Right Anterior Insula.
Poster presented at the 12th International Conference on Music Perception and Cognition and the 8th Triennial Conference of the European Society for the Cognitive Sciences of Music. [pdf] (2012). Music Listening from an Ecological Perspective. In
Cortex, 47(9), 1068-1081. [abstract] [link] (2011). Emotion rendering in music: Range and characteristic values of seven musical variables.
8th Sound and Music Computing Conference, Padova, Italy. [pdf] (2011). A Comparison of Perceptual Ratings and Computed Audio Features. In
Gemessene Interpretation - Computergestützte Aufführungsanalyse im Kreuzverhör der Disziplinen (pp. 237-253). Mainz: Schott 2011, (Klang und Begriff 4). [pdf] (2011). Perceptual ratings of musical parameters. In von Loesch, H., & Weinzierl, S. (Eds.),
Front. Hum. Neurosci. Conference Abstract: Tuning the Brain for Music. Helsinki, Finland. [abstract] (2009). How fast is the tempo in a happy music performance?. In
Front. Hum. Neurosci. Conference Abstract: Tuning the Brain for Music. Helsinki, Finland. [abstract] [link] (2009). Enabling emotional expression and interaction with new expressive interfaces. In