# Deep Learning-Based Acoustic Echo Cancellation for Surround Sound Systems
## 5 Experimental Results and Discussions  
### Experiment Settings  
The English reading speech of the DNS-challenge dataset [32] was used as the near-end and the far-end reference signals to perform experiments in the surround AEC situation, which was derived from Librivox, consisting of 65,348 clean clips from 1948 speakers. Each speaker was taken from about 33 utterances with about 30 s for each. Eighty percentages of speakers were used for training and the remaining twenty percentages for testing. For  
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each training sample, two speakers were randomly selected, and one was used as the far-end speaker and the other was used as the near-end speaker. We randomly cut 12 s long segments from each utterance of the far-end speaker, and the segment was used as the far-end speech. For the near-end speech, we randomly cut 3 s long segments from each utterance of the near-end speaker, and this segment was zero-padded on both sides to ensure that each near-end speech had the same duration as the far-end speech. The zero-padding operation was used to simulate the single-talk scene in real-world scenarios. The RIRs were generated using the image method [33]. In the far-end room, four microphones with different directivities were used to simulate an Ambisonics recording device located in the center of the room, including an omni-directional microphone, dubbed W, and three figure-of-eight directional microphones, dubbed X, Y and Z, respectively. Signals recorded by these four microphones constitute the B-format signal. Thus, for each sound source and Ambisonics microphone pair, we can get four RIRs, which were then defined as an Ambisonic RIRs group. In the near-end room, the RIRs were generated according to the position of the microphone, its directivity, and loudspeakers. To improve the generalization capacity of the DNN, the length and width of the simulated rooms were randomly sampled from \([3,10]\) m with \(1\) m interval and the height was sampled form \([3,5]\) m. In each simulated room, the reverberation time RT\({}_{60}\) value was randomly sampled from \(\{0.3,0.5,0.6\,\mathrm{s},0.7\,\mathrm{s},0.9\,\mathrm{s}\}\). The locations of the microphones and loudspeakers in the simulated room are shown in Figure 4, where the 5.1 surround sound system without the center and subwoofer channels was taken into consideration and the microphones were fixed in the center of each simulated room. As illustrated in Figure 4, four surround loudspeakers \(p_{1}\)-\(p_{4}\) were used and \(\alpha\) represents the angle between loudspeakers and the horizontal axis. \(\lambda\) represents the distance between the loudspeakers and microphones. For standard (ITU-R BS 77) 5.1 surround set-up [34], the \(\alpha\) angles for \(p_{1}\)-\(p_{4}\) were set to \(\{190^{\circ},120^{\circ},60^{\circ},350^{\circ}\}\). The nonstandard 5.1 surround set-up was also considered. In the nonstandard conditions, the \(\alpha\) angle for loudspeaker \(p_{1}\) was randomly sampled from \([190^{\circ},260^{\circ}]\) with \(10^{\circ}\) interval, and similarly, the \(\alpha\) ranges for \(p_{2},p_{3},p_{4}\) were set to be \([100^{\circ},170^{\circ}]\), \([10^{\circ},80^{\circ}]\) and \([280^{\circ},350^{\circ}]\) with \(10^{\circ}\) interval, respectively. \(\lambda\) was sampled from \(\{1\,\mathrm{m},1.2\,\mathrm{m},1.5\,\mathrm{m}\}\). In the far-end room, the angle between the speaker and horizontal axis was randomly sampled from \([10^{\circ},360^{\circ}]\) with \(10^{\circ}\) interval, and the distance between the speakers and microphones was sampled from \(\{0.3\,\mathrm{m},0.5\,\mathrm{m},0.7\,\mathrm{m},1\,\mathrm{m},1.2\,\mathrm{m}\}\).