Knowledge Commons of Institute of Automation,CAS
Adaptive Dereverberation Using Multi-channel Linear Prediction with Deficient Length Filter | |
Li GJ(李冠君); Liang S(梁山); Nie S(聂帅); Liu WJ(刘文举) | |
2019 | |
会议名称 | icassp |
会议日期 | 2019 |
会议地点 | 英国 |
摘要 | In almost all adaptive dereverberation algorithms based on the multi-channel linear prediction (MCLP) model, it is assumed that the filter length can cover the reverberation time. However, in many practical situations, a deficient length filter, whose length is less than the reverberation time, is employed in consideration of computational cost. A deficient length filter fails to fully model the late reverberation, resulting in degraded performance. In this paper, we present a new MCLP-based adaptive dereverberation algorithm to improve the dereverberation performance when using a deficient length filter. We introduce a gain and use the filter coefficients estimated from the previous frame to track the MCLP modeling errors of the current frame. The gain and the filter coeffi-cients are jointly optimized and solved by using an alternating minimization technique. Experimental results show the superiority of the proposed algorithm. The shorter the filter length is, the more advantageous the proposed algorithm is. |
七大方向——子方向分类 | 语音识别与合成 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/44843 |
专题 | 多模态人工智能系统全国重点实验室_智能交互 |
作者单位 | Institute of Automation, Chinese Academy of Sciences |
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 | Li GJ,Liang S,Nie S,et al. Adaptive Dereverberation Using Multi-channel Linear Prediction with Deficient Length Filter[C],2019. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
19icassp_降混响.pdf(874KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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