A cluster analysis of benchmark acoustic features on Brazilian music
Resumo
In this work, we extend a standard and successful acoustic feature extraction approach based on trigger selection to examples of Brazilian Bossa-Nova and Heitor Villa Lobos music pieces. Additionally, we propose and implement a computational framework to disclose whether all the acoustic features extracted are statistically relevant, that is, non-redundant. Our experimental results show that not all these well-known features might be necessary for trigger selection, given the multivariate statistical redundancy found, which associated all these acoustic features into 3 clusters with different factor loadings and, consequently, representatives.
Palavras-chave:
Brain-Computer Interfaces and Physiological Signals, Music Information Retrieval, Music Perception, Psychoacoustics and Cognition
Referências
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Vinoo Alluri, Petri Toiviainen, Iiro P Jääskeläinen, Enrico Glerean, Mikko Sams, and Elvira Brattico. Large-scale brain networks emerge from dynamic processing of musical timbre, key and rhythm. Neuroimage, 59(4):3677–3689, 2012.
Oliver Lartillot. MIRtoolbox 1.6.1 Users Manual, 2014.
Richard A. Johnson and Dean W. Wichern. Applied Multivariate Statistical Analysis. Pearson, 6th edition, 2007.
Andjela Markovic, Jürg Kühnis, and Lutz Jäncke. Task context influences brain activation during music listening. Frontiers in human neuroscience, 11:342, 2017.
Pasi Saari, Iballa Burunat, Elvira Brattico, and Petri Toiviainen. Decoding musical training from dynamic processing of musical features in the brain. Scientific Report, 708(8):1–12, 2018.
Peter Vuust, Elvira Brattico, Miia Sppanen, Risto Naatanen, and Mari Tervaniemi. The sound of music: Differentiating musicians using a fast, musical multi-feature mismatch negativity paradigm. Neuropsychologia, 50(7):1432–1443, June 2012.
C.A. Mikutta, G. Maissen, A. Altorfer, W. Strik, and T. Koenig. Professional musicians listen differently to music. Neuroscience, 268:102 – 111, 2014.
Vinoo Alluri, Petri Toiviainen, Iiro P Jääskeläinen, Enrico Glerean, Mikko Sams, and Elvira Brattico. Large-scale brain networks emerge from dynamic processing of musical timbre, key and rhythm. Neuroimage, 59(4):3677–3689, 2012.
Oliver Lartillot. MIRtoolbox 1.6.1 Users Manual, 2014.
Richard A. Johnson and Dean W. Wichern. Applied Multivariate Statistical Analysis. Pearson, 6th edition, 2007.
Publicado
25/09/2019
Como Citar
FERREIRA, Leonardo; RIBEIRO, Estela; THOMAZ, Carlos.
A cluster analysis of benchmark acoustic features on Brazilian music. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO MUSICAL (SBCM), 17. , 2019, São João del-Rei.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
p. 194-196.
DOI: https://doi.org/10.5753/sbcm.2019.10444.
