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Table 1 AUC values of the evaluated VAD algorithms under −5 dB SNR

From: Voice activity detection algorithm based on long-term pitch information

Noise

Sohn

Harmfreq

LTSD

LTSV

LSFM

LTPD

factory1

0.5538

0.5542

0.5978

0.8223

0.7113

0.8998

factory2

0.8702

0.8678

0.8508

0.9139

0.9190

0.9266

leopard

0.9608

0.9608

0.8721

0.9555

0.9623

0.9435

m109

0.9182

0.9096

0.8787

0.9653

0.9587

0.9500

opsroom

0.8183

0.8065

0.8498

0.9103

0.8561

0.8696

f16

0.8614

0.8587

0.8794

0.9296

0.8997

0.9316

buccaneer1

0.7612

0.7505

0.8471

0.9163

0.7921

0.9382

buccaneer2

0.8162

0.8119

0.8794

0.9494

0.9086

0.9495

babble

0.7687

0.7676

0.8556

0.7310

0.6873

0.7788

engine

0.8556

0.8521

0.9036

0.9546

0.8791

0.9069

hfchannel

0.8814

0.8797

0.9134

0.9480

0.8626

0.9312

machinegun

0.5934

0.5869

0.7860

0.7481

0.3423

0.9380

pink

0.7802

0.7776

0.8609

0.9434

0.8777

0.9481

volvo

0.9594

0.9594

0.9327

0.9273

0.9501

0.9561

white

0.8601

0.8572

0.8901

0.9609

0.9096

0.9521

average

0.8172

0.8134

0.8532

0.9051

0.8352

0.9213

  1. Note: The italicized numbers mean the best performance among all evaluated algorithms with the specific noise