## 4 Experiments
### Music Identification Experiment
#### 4.2.4 Music Identification Results
Fingerprinting features appear up to 5512 Hz by the setting of the identification system. These figures show that MDenseNet and MMDenseNet are poorly identified despite high SDR. In _Result 1_ of the figure, the separated signal by MMDenseNet with the second-highest SDR fails to be identified. However, the proposed architecture with the same SDR performance as MMDenseNet is successfully identified. In _Result 2_ of the figure, identification is successful although MDenseNet produces lower SDR than MMDenseNet. In contrast, MMDenseNet has the highest SDR but fails to be identified. Figure 10: _Cont._  
Figure 10: Music identification results and fingerprinting plots at spectrogram. The horizontal axis of the spectrogram represents time (0–12 s) and the vertical axis represents frequency (0–8000 Hz). The matching result and the SDR of the signal are displayed under each plot. The violet line is the fingerprinting of the query, and the black line is the fingerprinting that matches the reference. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Architecture** & **SNR** & **0 dB** & **–10 dB** \\ \hline Mix & 43.38 & 4.59 \\ U-Net & 42.33 & 19.38 \\ Wave-U-Net & 54.77 & 26.89 \\ MDenseNet & 52.57 & 28.44 \\ MMDenseNet & 49.66 & 26.67 \\ MMDenseLSTM & 67.94 & 44.96 \\ Proposed & **71.91** & **48.03** \\ Oracle & & 95.92 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Music identification accuracy (%). At the spectrogram in Figure 10, we can see discontinuous horizontal lines in MDenseNet and MMDenseNet. There is a discontinuous horizontal line at the 6500 Hz frequency of the MDenseNet spectrogram. This distortion is not frequent, and the discontinuous horizontal line appears at 6500 Hz in MMDenseNet. In addition, MMDenseNet notices an additional discontinuous horizontal line in the middle (4000 Hz) of the spectrogram. Placing an excessive number of parameters in each frequency band in parallel, such as MMDenseNet, is not effective for increasing the receptive field and introduces distortion on the spectrogram. This distortion of the spectrogram has a small effect on SDR but is an obstacle to extract for fingerprinting features in music identification. Designing to apply convolution to each band of the spectrogram like the multi-band block of the proposed structure can prevent distortion and effectively increase the receptive field. In the spectrogram of the proposed architecture, we can see that no distortion occurs. Even with these discontinuous horizontal lines, the separation performance of MMDenseNet is higher than that of MDenseNet because the SDR is sensitive to the low-frequency band of the spectrogram. Additional experiments in this regard are covered in the next subsection. The high identification performance of Wave-U-Net is expected to be related to the receptive field. A large receptive field of the network is advantageous for maintaining the peak points of the estimated spectrogram. Wave-U-Net has 12 down-sampling processes in the signal domain. The proposed architecture that effectively increases the receptive field by dilated convolution and down-sampling shows the best performance in identification as well as high SDR.