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The seven papers in this special issue cover various far-field speech processing techniques including speech enhancement, separation and recognition, and their integration. In most of the methods, multichannel speech processing is an essential component to achieve state-of-the-art performance. Deep learning techniques significantly enhances the performance of these techniques. Furthermore, analyses and databases facilitate research and development of such techniques. Although there has been significant progress in the field of far-field speech processing, there still remain challenging issues including speaker diarization, audio synchronization, dynamic environment (e.g., moving speakers/microphones in a robot scenario). On the other hand, recent progress in end-to-end speech processing and the use of multimodal sensor data could provide alternative solutions for these challenges. We hope this special issue becomes a trigger for the community to tackle these challenging and exciting far-field speech processing technologies.
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