基于聚焦信号子空间估计导向矢量的干扰声源抑制方法
Suppression Method of the Interference Sound Sources by Estimated Steering Vector Based on the Focusing Signal Subspace
- 电子学报 2023年51卷第1期 页码：76-85
- 作者机构：
北京工业大学信息学部语音与音频信号处理实验室，北京 100124
- 作者简介：
[ "周 静 男，1993年生于四川广安.现为北京工业大学博士研究生.主要研究方向为语音增强.E-mail: zhoujing@emails.bjut.edu.cn" ]
[ "鲍长春（通讯作者） 男，1965年生于内蒙古赤峰，中国电子学会会士，IEEE高级会员.现为北京工业大学教授、博士生导师.主要研究方向为语音编码与语音增强.E-mail: chchbao@bjut.edu.cn" ]
[ "张 旭 女，1995生于内蒙古乌兰察布.现为北京工业大学博士研究生.主要研究方向为语音分离.E-mail: zhangxu@emails.bjut.edu.cn" ]
- 基金信息：国家自然科学基金(61831019)
DOI：10.12263/DZXB.20220210
中图分类号： TN912收稿：2022-03-01，
修回：2022-10-03，
纸质出版：2023-01-25
- 稿件说明：
移动端阅览
周静,鲍长春,张旭.基于聚焦信号子空间估计导向矢量的干扰声源抑制方法[J].电子学报,2023,51(01):76-85.
ZHOU Jing,BAO Chang-chun,ZHANG Xu.Suppression Method of the Interference Sound Sources by Estimated Steering Vector Based on the Focusing Signal Subspace[J].ACTA ELECTRONICA SINICA,2023,51(01):76-85.
周静,鲍长春,张旭.基于聚焦信号子空间估计导向矢量的干扰声源抑制方法[J].电子学报,2023,51(01):76-85. DOI： 10.12263/DZXB.20220210.
ZHOU Jing,BAO Chang-chun,ZHANG Xu.Suppression Method of the Interference Sound Sources by Estimated Steering Vector Based on the Focusing Signal Subspace[J].ACTA ELECTRONICA SINICA,2023,51(01):76-85. DOI： 10.12263/DZXB.20220210.
摘要
针对最小方差无失真响应（Minimum Variance Distortionless Response
MVDR）波束形成器对导向矢量失配较敏感的问题，本文提出了一种有效的干扰声源抑制方法.该方法首先将语音信号的频带划分为多个子带，通过聚焦信号子空间方法估计各子带的声源到达方向（Direction of Arrival
DOA），并采用统计直方图估计各声源的初始DOA；其次，为了减小导向矢量失配，利用声源的空间稀疏性，通过Capon功率构建目标声源导向矢量估计的代价函数，约束目标声源导向矢量远离干扰声源空间；最后，根据估计的导向矢量，估计干扰声源加噪声协方差矩阵，以获得MVDR波束形成器的权重.基于TIMIT语料库的实验结果证明，提出的干扰声源抑制方法的输出信干噪比（SINR）及语音质量感知评价（PESQ）优于参考方法，具有更佳的抗导向矢量失配性能.
Abstract
Based on the problem that the minimum variance distortionless response (MVDR) beamformer is very sensitive to the mismatch of the steering vector
an effective method of suppressing the interference sound sources is proposed in this paper. First
the bandwidth of speech signal is divided into multiple sub-bands
and the direction of arrival (DOA) of sound sources at each sub-band is estimated by the focusing signal subspace method. Specially
the initial DOA of each sound source is estimated via statistical histogram. Second
in order to reduce the mismatch of the steering vector
based on the spatial sparsity of sound sources
the cost function used for the steering vector estimation of the target sound source is constructed by Capon power so that the steering vector of the target sound source is constrained away from the space of interference sound sources. Finally
the covariance matrix of interference sound source plus noise is estimated based on the estimated steering vector for obtaining the weights of the MVDR beamformer. The experimental results on the TIMIT corpus show that the proposed method outperforms the reference methods on the tests of the output signal to interference-plus-noise ratio (SINR) and the perceptual evaluation of speech quality (PESQ) and has a better performance for preventing the mismatch of the steering vector.
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references
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