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Table 7 Best results after parameter tuning for arousal and valence tasks with according settings (feature set, feature selection method, and percentage of features). Top, overall best settings; Mid, overall best with only the EmoFt set; Bottom, overall best with only the EmoFt set and linear kernel SVM

From: Emotion in the singing voice—a deeperlook at acoustic features in the light ofautomatic classification

Dimension UAR [%] Setting
Overall best results   
Arousal 61.7 ComParE, CC-FS (50 %), linear, C=0.05
Valence 52.9 ComParE, CC-FS (10 %), linear, C=1.0
EmoFt set best results   
Arousal 60.1 EmoFt, CC-FS (50 %), RBF kernel, C=1.0
Valence 48.0 EmoFt, CC-FS (50 %), RBF kernel, C=1.0
EmoFt set, only linear kernel SVM, best results   
Arousal 58.0 ComParE, SPKSTD-CC (30 %), linear, C=0.05
Valence 45.3 ComParE, all features, linear, C=1.0