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The initial experimental results highlight further requirement to improve the reverberation gain by the pulse design with the slow moving target.
These results indicate that the performance of environment identificat7ion is improved by using estimated reverberation in training the DNN.
Such a claim can be supported, for example, by the fact that the 1-ch system developed by Cauchi et al. [19] is the only one among 11 submitted 1-ch systems that significantly reduced the perceived amount of reverberation and improved overall quality, whereas their system ranked 5th in terms of FWSegSNR score.
Multichannel systems: Many systems significantly reduced the perceived amount of reverberation and significantly improved the overall quality.
The results showed that while subtracting the mean of the log magnitude spectrum improved ASR performance, the improvement was not sufficient, especially in the presence of significant late reverberation.
Fidelity is improved by error correction and activity-reverberation limitation.
In our earlier studies[19], several auditory processing-motivated features have shown considerably improved robustness for both additive noise and reverberation.
Ten RIRs were simulated using an improved image-source method (ISM) [39] with reverberation time (RT60) ranging from 0.1 to 1.0 s, with an increment of 0.1 s.
The single-channel scenario is particularly challenging as illustrated by the results of the REVERB challenge workshop [27], in which most contributions succeeded to reduce reverberation but only a few improved the speech quality [4, 12].
The one-stage dereverberation and denoising method improved the speech recognition performance under all reverberant and noisy speech at each SNR level and reverberation time.
The validity of the proposed improved approach is illustrated through a numerical comparison between the improved method's results and the exact solution obtained from the reverberation-ray matrix method.
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