표 3 / Table 3 REVERB challenge 2014 데이터에 대한 실험 결과(word error rate, %) / Experimental results on REVERB challenge 2014 evaluation set

Experimental condition SimData RealData
Room1 Room2 Room3 Average Room1 Average
Acoustic model Near Far Near Far Near Far Near Far
CNN 5.74 6.74 7.28 12.42 8.16 15.00 9.22 24.66 26.06 25.36
VDCNN 4.88 5.54 5.81 8.80 6.34 10.26 6.94 19.35 20.26 19.81
DenseNet 5.00 5.20 5.29 8.15 6.18 8.90 6.45 18.62 19.51 19.07
MR-DenseNet 4.47 5.12 5.22 7.43 5.71 8.73 6.11 17.66 18.50 18.08
reverberant voice enhancement and recognition benchmark: REVERB, convolutional neural network: CNN; very deep convolutional neural network: VDCNN, multi-resolution DenseNet: MR-DenseNet