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Table 9 Performance results of TLBO algorithm, c-bic, c-sid, and p-asr systems obtained on the RT-04F and ESTER datasets. Scores are given for missed speech (MS), false alarms (FA), speaker errors (SPK), and overall diarization error rate (DER). #REF and #Sys are, respectively, the reference and system speaker number

From: Integration of evolutionary computation algorithms and new AUTO-TLBO technique in the speaker clustering stage for speaker diarization of broadcast news

RT-04F dev1 dataset

System

Method

#Ref

#Sys

MS

FA

SPK

Overall DER

Dev1

c-sid

121

161

0.4

1.3

5.4

7.1

TLBO algorithm

121

161

0.383

1.116

5.75

7.249

Show

ABC

27

35

1.4

1.1

12.2

14.7

VOA

20

22

0.2

1.1

2.1

3.4

PRI

27

29

0.1

0.8

2.7

3.6

NBC

21

30

0.1

0.9

11.5

12.5

CNN

16

19

0.4

1.2

5.4

7.0

MNB

10

13

0.1

1.6

0.6

2.3

Dev2

c-sid

90

130

0.5

3.1

4.1

7.6

TLBO algorithm

90

130

0.516

3.083

4.216

7.725

Show

CSPN

3

4

0.2

2.8

0.1

3.1

CNN

17

20

0.6

4.1

4.9

9.6

PBS

27

28

0.1

2.6

7.2

10.0

ABC

23

26

2.1

6.7

12.1

20.9

CNNHL

9

15

0.0

1.4

0.3

1.7

CNBC

11

16

0.1

0.9

0.7

1.7

RT-04F dev2 dataset

 c-bic

–

–

0.4

1.8

14.8

17.0

 c-sid (δ = 0.1)

–

–

0.4

1.8

6.9

9.1

 p-asr

–

–

0.6

1.1

5.2

7.6

 TLBO algorithm

–

–

0.6

1.8

7.8

10.2

ESTER development dataset

 c-bic

–

–

0.7

1.0

12.1

13.8

 c-sid (δ = 1.5)

–

–

0.7

1.0

9.8

11.5

 TLBO algorithm

–

–

0.6

1.0

9.7

12.3

Post-evaluation result on ESTER dataset

 c-sid (δ = 2.0)

–

–

0.7

1.0

7.4

9.1