• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>European Conference on Speech Communication and Technology v.4; 20010903-20010907; Aalborg; DK >Blind Source Separation for Speech Based on Fast-Convergence Algorithm with ICA and Beamforming
【24h】

Blind Source Separation for Speech Based on Fast-Convergence Algorithm with ICA and Beamforming

机译：基于ICA和波束赋形的快速收敛算法的语音盲源分离

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

We propose a new algorithm for blind source separation (BSS), in which independent component analysis (ICA) and beamforming are combined to resolve the low-convergence problem through optimization in ICA. The proposed method consists of the following three parts: (1) frequency-domain ICA with direction-of-arrival (DOA) estimation, (2) null beamforming based on the estimated DOA, and (3) integration of (1) and (2) based on the algorithm diversity in both iteration and frequency domain. The inverse of the mixing matrix obtained by ICA is temporally substituted by the matrix based on null beamforming through iterative optimization, and the temporal alternation between ICA and beamforming can realize fast- and high-convergence optimization. The results of the signal separation experiments reveal that the signal separation performance of the proposed algorithm is superior to that of the conventional ICA-based BSS method, even under reverberant conditions.
机译：我们提出了一种盲源分离（BSS）的新算法，该算法将独立分量分析（ICA）和波束成形结合起来，通过ICA中的优化来解决低收敛性问题。所提出的方法包括以下三个部分：（1）具有到达方向（DOA）估计的频域ICA；（2）基于估计的DOA的零波束成形；以及（3）（1）和（ 2）基于迭代和频域中的算法多样性。通过迭代优化，将基于ICA的混合矩阵的逆矩阵暂时替换为基于零波束成形的矩阵，并且ICA与波束成形之间的时间交替可以实现快速和高收敛性优化。信号分离实验的结果表明，即使在混响条件下，该算法的信号分离性能也优于传统的基于ICA的BSS方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号