Cross-domain cooperative deep stacking network for speech separation
文献类型：会议论文
| 作者 | Wei Jiang1; Shan Liang1 ; Like Dong2; Hong Yang2; Wenju Liu1; Yunji Wang3
|
| 出版日期 | 2015 |
| 会议日期 | April 19-24, 2015 |
| 会议地点 | Brisbane, Australia |
| 关键词 | Speech Separation Cross-domain Cooperative Structure Deep Stacking Network Deep Neural Network |
| 英文摘要 | Nowadays supervised speech separation has drawn much attention and shown great promise in the meantime. While there has been a lot of success, existing algorithms perform the task only in one preselected representative domain. In this study, we propose to perform the task in two different time-frequency domains simultaneously and cooperatively, which can model the implicit correlations between different representations of the same speech separation task. Besides, many time-frequency (T-F) units are dominated by noise in low signal-to-noise ratio (SNR) conditions, so more robust features are obtained by stacking features of original mixtures with that extracted from separated speech of each deep stacking network (DSN) block, which can be regarded as a denoisedversionoftheoriginalfeatures. Quantitativeexperiments show that the proposed cross-domain cooperative deep stacking network (DSN-CDC) has enhanced modeling capability as well as generalization ability, which outperforms a previous algorithm based on standard deep neural networks. |
| 会议录 | EI
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/12361]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_机器人视觉团队 |
| 通讯作者 | Wenju Liu |
| 作者单位 | 1.NLPR, Institute of Automation, Chinese Academy of Sciences 2.Electric Power Research Institute of ShanXi Electric Power Company, China State Grid Corp 3.Electrical and Computer Engineering Department, The University of Texas at San Antonio, USA |
| 推荐引用方式 GB/T 7714 | Wei Jiang,Shan Liang,Like Dong,et al. Cross-domain cooperative deep stacking network for speech separation[C]. 见:. Brisbane, Australia. April 19-24, 2015. |
入库方式： OAI收割
来源：自动化研究所
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