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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