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Table 6 Within-corpus results for binary classification on the USC IEMOCAP database

From: Articulation constrained learning with application to speech emotion recognition

 

SVM

ACO

ACL

Best target

Best group

BCUAR

Arousal

/AA/

65.81

67.43

69.18*

72.60 (LPH, Z)

70.28 (LPH)

65.44

/AE/

63.67

64.24

65.40

66.95 (LPH, X)

65.74 (LPH)

63.65

/IY/

65.27

66.36

65.85

67.90 (LIP, Y)

67.70 (LIP)

66.22

/UW/

62.49

63.90

64.44

67.60 (LPH, Z)

66.50 (LIP)

69.03

FULL

72.96

72.58

73.52

75.04 (CHN, X)

75.12 (CHN)

50.47

Valence

/AA/

59.29

60.47

60.68

64.69 (LIP, Z)

63.01 (CHW)

51.21

/AE/

57.20

57.61

59.06*

61.49 (LPW, X)

60.02 (CHW)

54.83

/IY/

59.61

60.36

61.34

62.85 (CHN, Y)

61.85 (LPW)

56.88

/UW/

61.20

63.17

63.62

64.42 (CHW, X)

63.95 (LIP)

56.25

FULL

60.34

61.74

62.16

63.37 (LPH, Z)

62.95 (LPW)

60.45

  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, and the by-chance unweighted average recall (BCUAR). *Statistically significant improvement (p < 0.05) over compared methods