| Paper ID | SPE-18.5 |
| Paper Title |
REAL-TIME SPEECH ENHANCEMENT FOR MOBILE COMMUNICATION BASED ON DUAL-CHANNEL COMPLEX SPECTRAL MAPPING |
| Authors |
Ke Tan, The Ohio State University, United States; Xueliang Zhang, Inner Mongolia University, China; DeLiang Wang, The Ohio State University, United States |
| Session | SPE-18: Speech Enhancement 4: Multi-channel Processing |
| Location | Gather.Town |
| Session Time: | Wednesday, 09 June, 14:00 - 14:45 |
| Presentation Time: | Wednesday, 09 June, 14:00 - 14:45 |
| Presentation |
Poster
|
| Topic |
Speech Processing: [SPE-ENHA] Speech Enhancement and Separation |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
Speech quality and intelligibility can be severely degraded by background noise in mobile communication. In order to attenuate background noise, speech enhancement systems have been integrated into mobile phones, and a microphone array is typically deployed to improve the enhancement performance. This paper proposes a novel approach to real-time speech enhancement for dual-microphone mobile phones. Our approach employs a causal densely-connected convolutional recurrent network to perform dual-channel complex spectral mapping. We apply a structured pruning technique for compressing the model without significantly affecting the enhancement performance. This leads to a real-time enhancement system for on-device processing. Evaluation results show that the proposed approach substantially advances the performance of an earlier approach to dual-channel speech enhancement for mobile communication. |
