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Table 3 Within-corpus results for binary classification on the USC EMA database

From: Articulation constrained learning with application to speech emotion recognition

Vowel

SVM

ACO

ACL

Best target

Best group

BCUAR

Arousal

/AA/

95.26

95.12

93.46

93.84 (JAW, VEL, Y)

93.51 (JAW)

54.51

/AE/

91.09

91.47

91.88

91.74 (LIP, POS, X)

92.01 (LIP)

53.16

/IY/

95.34

95.59

95.74

95.57 (JAW, POS, X)

95.80 (JAW)

53.35

/UW/

94.49

93.64

93.85

93.64 (TNG, ACC, X)

94.41 (LIP)

57.75

FULL

99.51

99.51

99.13

99.64 (LIP, POS, X)

99.25 (TNG)

52.88

Valence

/AA/

78.38

77.89

79.46*

79.38 (JAW, ACC, Y)

79.34 (LIP)

53.17

/AE/

76.75

78.40

78.34

78.26 (TNG, VEL, X)

78.20 (JAW)

52.47

/IY/

70.14

69.45

73.04*

73.90 (LIP, VEL, Y)

73.01 (LIP)

54.02

/UW/

76.25

72.01

76.13*

77.63 (JAW, ACC, X)

76.30 (LIP)

53.44

FULL

92.85

92.79

95.11*

95.33 (TNG, VEL, X)

95.31 (TNG)

52.68

  1. The UAR is expressed in percentage. The columns of the table represent results from several models: support vector machine (SVM), acoustic only model (ACO), articulation constrained learning (ACL), best target using ACL, best group of targets using ACL, the by-chance unweighted average recall. *Statistically significant improvement(p<0.05) over compared methods