# Crossband Filtering for Weighted Prediction Error-Based Speech Dereverberation
## 4 Experimental Results  
### Data and Setup  
To validate the performance of the proposed method, we collected a dataset of 10 clean speech signals from the Deep Noise Suppression (DNS) challenge dataset [31]. To emulate realistic acoustic conditions, we generated acoustic channel RIRs using the image model method [32]. The reverberation levels were controlled by adjusting the wall reflection coefficient parameter. The experimental setup consisted of a uniform linear array with four microphones positioned in a room measuring 6 m by 8 m by 3 m. The speaker was located at coordinates (5, 4, 1.7), while the microphones were placed at different positions along the x-axis. More specifically, the microphones were positioned at \((x,2,1.6)\), where \(x\) was uniformly distributed from 2.936 to 2.999. The reverberation time (T60) of approximately 300 ms was attained by configuring the absorption coefficient of the room's walls. This choice was informed by our observation that lower values of T60 resulted in a relatively inconspicuous reverberation effect, accompanied by an insubstantial enhancement through the proposed method. Furthermore, various room configurations were comprehensively explored, encompassing alterations in the microphone array's spatial arrangement, inter-microphone spacing, and the speaker's position. More specifically, we conducted a comprehensive exploration of microphone spacing, ranging from 1 cm to 4 cm. Additionally, we meticulously examined various configurations involving offsets in both the microphone array and the speaker's position along both the \(x\)-axis and \(y\)-axis. Remarkably, despite these deliberate modifications, the experimental outcomes exhibited remarkable consistency across configurations. Given this consistency, we present the outcomes from a representative configuration for brevity and clarity. The clean speech signals and RIRs were sampled at 16 kHz. The multichannel observed signals were generated by convolving the RIRs with the single-channel clean speech signals. Spectral analysis was performed using STFTs with a 512-length Blackman window and a shift of 128 samples between frames. By meticulously designing this experimental setup, we aimed to establish a reliable basis forevaluating the proposed method's performance. Including diverse speech signals, accurate RIR generation, and careful control of reverberation levels contributed to a comprehensive assessment of the method's effectiveness in enhancing speech signals. Additionally, when performing WPE, we set the predefined prediction delay to \(D=3\) to maintain consistency across the experiments. Using Algorithm 1, we have empirically determined that setting the number of iterations to \(N=3\) is adequate to achieve the convergence of the filter coefficients and the variances. Based on the definition of the prediction filters of order \(L\) and \(\tilde{L}\) in Section 3, we conducted two types of experiments. 1. Length extension (Ext. ): In this first version of the proposed method, denoted as the \"length extension\", we set the parameter \(L_{\text{bb}}\) equal to \(L\). This design choice ensured that the samples from the crossband components, which introduced additional computational complexity, were included in the analysis. This specific experiment aimed to demonstrate the significance of the information contained in the crossband components in enhancing the dereverberation performance. While it did introduce computational complexity, this experimental approach allowed us to assess the true potential and effectiveness of the proposed method by leveraging the information-rich crossband components. 2. Length preservation (Pres. ): In the second version of the proposed method, denoted as \"length preservation\", we established \(\tilde{L}\) to equal \(L\). To maintain comparable computational complexity to the conventional WPE method, we introduced a modification by discarding the two most recent samples from the band-to-band component for every sample utilized in the crossband components.