Table 2 Performance of our proposed methods and several typical RES methods

Artificial speech

LAEC

1.48

−2.60

0.622

LSTM

2.14

6.33

0.780

MSTasNet

2.54

11.6

0.857

DSDPRNN_ty

2.61

12.3

0.866

DSDPRNN_tx

2.66

12.8

0.876

DSDPRNN_fy

2.75

12.4

0.880

DSDPRNN_fx

2.74

12.5

0.882

Artificial music

LAEC

1.48

−2.90

0.634

LSTM

2.08

5.46

0.755

MSTasNet

2.43

10.7

0.830

DSDPRNN_ty

2.50

11.5

0.842

DSDPRNN_tx

2.61

12.6

0.865

DSDPRNN_fy

2.62

11.4

0.857

DSDPRNN_fx

2.64

11.6

0.863

ER speech

LAEC

16.1

−2.05

0.697

LSTM

2.13

4.85

0.799

MSTasNet

2.66

11.6

0.890

DSDPRNN_ty

2.68

11.7

0.892

DSDPRNN_tx

2.62

11.5

0.887

DSDPRNN_fy

2.77

11.3

0.904

DSDPRNN_fx

2.66

10.6

0.895

ER music

LAEC

1.70

−1.12

0.730

LSTM

2.25

5.95

0.826

MSTasNet

2.72

12.2

0.898

DSDPRNN_ty

2.75

12.6

0.900

DSDPRNN_tx

2.68

12.3

0.897

DSDPRNN_fy

2.79

11.9

0.907

DSDPRNN_fx

2.76

11.7

0.907

LL speech

LAEC

1.95

1.67

0.806

LSTM

2.55

9.23

0.884

MSTasNet

2.99

15.0

0.932

DSDPRNN_ty

3.00

15.6

0.932

DSDPRNN_tx

2.87

14.9

0.920

DSDPRNN_fy

3.02

15.3

0.938

DSDPRNN_fx

3.04

15.7

0.938

LL music

LAEC

1.97

2.16

0.820

LSTM

2.60

9.07

0.889

MSTasNet

3.04

15.6

0.934

DSDPRNN_ty

3.07

16.0

0.935

DSDPRNN_tx

2.89

14.8

0.921

DSDPRNN_fy

3.12

15.8

0.944

DSDPRNN_fx

3.13

16.0

0.943