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- W3025300213 abstract "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." @default.
- W3025300213 created "2020-05-21" @default.
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- W3025300213 date "2019-09-25" @default.
- W3025300213 modified "2023-10-03" @default.
- W3025300213 title "A cluster analysis of benchmark acoustic features on Brazilian music" @default.
- W3025300213 cites W2078221232 @default.
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- W3025300213 doi "https://doi.org/10.5753/sbcm.2019.10444" @default.
- W3025300213 hasPublicationYear "2019" @default.
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