Knowledge Commons of Institute of Automation，CAS
| EXPLOITING SPECTRO-TEMPORAL STRUCTURES USING NMF FOR DNN-BASED SUPERVISED SPEECH SEPARATION | |
Shuai, Nie1; Shan, Liang1 ; Hao, Li2; XueLiang, Zhang2; ZhanLei, Yang1; WenJu, Liu1; LiKe, Dong3
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| 2016 | |
| 会议名称 | IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) |
| 会议录名称 | IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
| 页码 | 469-473 |
| 会议日期 | 2016 |
| 会议地点 | Shang Hai, China |
| 出版者 | IEEE |
| 摘要 | The targets of speech separation, whether ideal masks or magnitude spectrograms of interest, have prominent spectro-temporal structures. These characteristics are very worthy to be exploited for speech separation, however, they are usually ignored in previous works. In this paper, we use nonnegative matrix factorization (NMF) to exploit the spectro-temporal structures of magnitude spectrograms. With nonnegative constrains, NMF can capture the basis spectra patterns of speech and noise. Then the learned basis spectra are integrated into a deep neural network (DNN) to reconstruct the magnitude spectrograms of speech and noise with their nonnegative linear combination. Using the reconstructed spectrograms, we further explore a discriminative training objective and a joint optimization framework for the proposed model. Systematic experiments show that the proposed model is competitive with the previous methods in monaural speech separation tasks. |
| 关键词 | Speech Separation Deep Neural Network Nonnegative Matrix Factorization Spectro-temporal Structures |
| 收录类别 | EI |
| 语种 | 英语 |
| 文献类型 | 会议论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/11023 |
| 专题 | 多模态人工智能系统全国重点实验室_机器人视觉 |
| 作者单位 | 1.National Laboratory of Patten Recognition, Institute of Automation, Chinese Academy of Sciences 2.College of Computer Science, Inner Mongolia University 3.Electric Power Research Institute of ShanXi Electric Power Company, China State Grid Corp |
| 第一作者单位 | 中国科学院自动化研究所 |
| 推荐引用方式 GB/T 7714 | Shuai, Nie,Shan, Liang,Hao, Li,et al. EXPLOITING SPECTRO-TEMPORAL STRUCTURES USING NMF FOR DNN-BASED SUPERVISED SPEECH SEPARATION[C]:IEEE,2016:469-473. |
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| ShuaiNie2016.pdf（408KB） | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 | ||
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