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- W1570504315 abstract "Is it easier to identify musicians by listening to their voic es or their music? We show that for a small set of pop and rock songs, automatically-located singing segments form a more reliable basis for classification than using the entire trac k, suggesting that the singer’s voice is more stable across dif ferent performances, compositions, and transformations d ue to audio engineering techniques than the instrumental background. The accuracy of a system trained to distinguish among a set of 21 artists improves by about 15% (relative to the basel ine) when based on segments containing a strong vocal component, whereas the system suffers by about 35% (relative) when music-only segments are used. In another experiment on a smaller set, however, performance drops by about 35% (relative) when the training and test sets are selected from different albums, suggesting that the system is learning al bum-specific properties possibly related to audio producti on techniques, musical stylistic elements, or instrumentati on, even when attention is directed toward the supposedly more stable vocal regions." @default.
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- W1570504315 date "2002-06-01" @default.
- W1570504315 modified "2023-09-23" @default.
- W1570504315 title "USING VOICE SEGMENTS TO IMPROVE ARTIST CLASSIFICATION OF MUSIC" @default.
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- W1570504315 doi "https://doi.org/10.7916/d8k64td6" @default.
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