Table 4 The recognition performance of the proposed GMM-HMM EASR system (in terms of WER (%)) for Persian ESD. The values of WER are obtained by applying different warping methods to various acoustic features extracted from different emotional utterances. The symbol * shows statistically significant cases (i.e., p value < 0.05)

MFCC

No Warping

42.30

24.54

36.08

29.70

26.43

31.81

Filterbank Warping

42.13

23.81

34.25

30.05

21.48^*

30.34

DCT Warping

28.20^*

22.34

31.32^*

18.78^*

18.25^*

23.78

Filterbank & DCT Warping

27.05^*

21.61^*

32.42^*

20.21^*

15.97^*

23.45

M-MFCC

No Warping

36.07

19.41

27.11

24.15

20.15

25.38

Filterbank Warping

34.26

17.95

25.82^*

23.79

20.72

24.51

DCT Warping

17.21^*

16.30

21.61^*

16.10^*

19.01

18.05

Filterbank & DCT Warping

22.79^*

15.93

24.73^*

17.35^*

20.53

20.27

ExpoLog

No Warping

37.87

16.12

26.01

26.83

20.34

25.43

Filterbank Warping

30.49^*

13.55^*

15.02^*

22.72^*

15.78^*

19.51

DCT Warping

37.54

14.65

25.64

27.55

20.34^*

25.13

Filterbank & DCT Warping

32.46^*

13.92^*

16.12^*

28.98

19.01^*

22.10

GFCC

No Warping

40.66

44.51

48.72

44.90

27.38

41.23

Filterbank Warping

39.67

43.77

47.44

44.01

27.19^*

40.42

DCT Warping

26.89^*

39.74^*

43.77

39.53

26.81

35.35

Filterbank & DCT Warping

28.36^*

40.84^*

45.60

40.79

29.09^*

36.94

PNCC

No Warping

3.93

5.13

5.31

6.80

5.70

5.37

Filterbank Warping

3.93

5.13

4.58

6.62

5.70

5.19

DCT Warping

4.10

5.13

4.40^*

6.26

4.56

4.89

Filterbank & DCT Warping

3.93^*

5.31^*

4.95

6.44

5.32^*

5.19