## 3 Experiment and Analysis
### Experiment Result Analysis  
#### 3.2.1 Effect of the Various SNR Conditions  
Figure 8 compares the distortion-noise ratio of frames with different methods while SNR is \(-5\) dB. The distortion of the enhanced speech signal was calculated using Equation (30), where \(k\) represents the \(k\)th frame and \(l\) is the length of the frame. \(y_{out}(n)\) and \(s_{spsech}(n)\) represent the output signal of the method and the clean desired speech signal without noise, respectively. Less distortion means better denoising performance of the method. Equation (31) calculates the distortion-noise ratio as the distortion divided by the pure noise energy. \[distortion(k)=\sum_{n=k\
eq l}^{(k+1)*l}\left[y_{out}(n)-s_{spsech}(n)\right] ^{2} \tag{30}\]  
\[p(k)=\left|\frac{distortion(k)}{noise(k)}\right|=\sum_{n=k\
eq l}^{(k+1)*l} \frac{\left[y_{out}(n)-s_{spsech}(n)\right]^{2}}{\left[s_{noise}(n)\right]^{ 2}} \tag{31}\]  
Figure 8 presents an enlarged view of Figure 8 from the 50 th to 100 th frames, which included two peaks of the speech frame energy. The figure shows that peaks of the signal distortion were generated using the GSC method when the energy of the speech frame was increased suddenly. The GSC-CC method could alleviate this problem, while the residual noise would increase at other frames where the speech energy is stable. The GSC-SN method could reduce the distortion of most frames caused by the residual noise, but the above-mentioned distortion problem with damage to the desired signal exists. The GSC-SN-MCC method could take advantage of the above methods to decrease both kinds of distortion of the enhanced signal. Figure 7: Experiment layout in the anechoic chamber. The maximum distortion occurred at the 83 rd frame in this case, as shown in Figure 8. Figure 9 presents the spectrum of signal distortion of the 83 rd frame where the fast Fourier transform was utilized. For convenience, the amplitude of the spectrum was normalized. Figure 9a shows the spectrum of signal distortion of the 83 rd frame over the entire frequency band with different methods. When a different method was employed, there were apparent differences in the amplitude from 500 Hz to 2000 Hz, where the speech energy was concentrated. Figure 9b shows the enlarged view of this frequency band. The distortion spectrum with the GSC-SN-MCC method was smaller and flatter than the conventional GSC method. Hence, the distortion of the enhanced signal caused by damaging the desired signal was reduced successfully using the proposed method. Tables 1 and 2 list the denoising performance of different methods under various SNR conditions. Table 1 lists the average of the distortion-noise ratio, and Table 2 presents the distortion value of the 83 rd frame (maximum distortion frame) under various conditions. For comparison, the average value of the distortion-noise ratio and the distortion value of the 83 rd frame was normalized to the result of the GSC method, which was one, as shown in Equations (32) and (33). Table 2 indicates that the GSC-CC method could reduce the peak value of the enhanced signal distortion effectively under most SNR conditions, except that the noise was too heavy that the speech energy barely affected the estimation of the residual noise. The GSC-SN method showed better performance under low SNR conditions (Table 1). The proposed GSC-SN-MCC method was a combination of the above two methods. The tables show that the proposed method could work effectively under  
Figure 8: Distortion–noise ratio of frames with different methods: (**a**) all frames; (**b**) from the 50 th to 100 th frame. Figure 9: Spectrum of the signal distortion of the 83 rd frame with different methods: (**a**) entire frequency band; (**b**) from 500 HZ to 2000 HZ. Tables 3 and 4 compare the performance of the different methods in various estimated noise directions. Table 3 shows that the performance of the GSC-SN method would decrease with the estimated noise direction far away from the actual noise direction.