| 扩散噪声下协方差矩阵重构的语音分离与降噪 |
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| 引用本文： | 曾庆宁,王师琦.扩散噪声下协方差矩阵重构的语音分离与降噪[J].声学学报,2021,46(5):775-784. |
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| 作者姓名： | 曾庆宁 王师琦 |
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| 作者单位： | 桂林电子科技大学 信息与通信学院 桂林 541004 |
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| 基金项目： | 国家自然科学基金项目(61961009)、广西自然科学基金重点项目(2016GXNSFDA380018)和“广西无线宽带通信与信号处理”重点实验室基金项目(GXKL06200107)资助 |
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| 摘 要： | 针对传统多通道语音分离算法在扩散噪声下性能下降的问题,提出了一种用于语音分离及降噪的空间协方差模型及参数估计方法。该方法将扩散噪声视为独立声源,利用由导向矢量重构的空间协方差矩阵建模目标声源的空间特性,并通过空间协方差分析方法估计用于语音分离的多通道维纳滤波器。同时,还提出了一种联合该方法的后置滤波器参数框架,为输出信号降噪和失真的折中提供了更多选择。在扩散噪声下的单目标和多目标实验中,所提方法的语音提取和分离性能都优于对比算法,联合参数的后置滤波器可提供更为符合人们要求的降噪语音,验证了所提模型与参数估计方法的有效性。
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| 关 键 词： | 语音分离 满秩协方差模型 扩散噪声 传声器阵列 空间协方差矩阵 |
| 收稿时间： | 2020-11-16 |
Covariance matrix reconstruction for speech separation and denoising in diffuse noise |
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| Affiliation: | Department of Information and Communication, Guilin University of Electronic Technology Guilin 541004 |
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| Abstract: | In order to improve the performance of multichannel speech separation algorithm in diffuse noise,a spatial covariance model and parameter estimation method for speech separation and noise reduction are proposed.In this method,diffuse noise is assumed to be an independent source,and the spatial characteristics of the target source are modeled by the spatial covariance matrix reconstructed from the steering vector,and the multichannel Wiener filter for speech separation is estimated by the spatial covariance analysis method.Moreover,a joint parameter framework of this method and postfilter is proposed,which provides more compromise selections between speech dereverberation and noise reduction for the output signal.In the experiments of single-source and multi-source in diffuse noise,the proposed method outperformed the conventional methods in speech extraction and separation.The postfilter with joint parameters provides more satisfactory denoised speech.This verified the effectiveness of the proposed model and parameter estimation method. |
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