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Real-time acoustic source separation based on Kalman filter
Wei YJ(魏阳杰); Wang Y(王义); He YQ(何玉庆)
作者部门机器人学研究室
会议名称2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA)
会议日期June 15-17, 2015
会议地点Auckland, New Zealand
会议录名称Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015
出版者IEEE
出版地Piscataway, NJ, USA
2015
页码1273-1278
收录类别EI ; CPCI(ISTP)
EI收录号20161202121295
WOS记录号WOS:000377208900231
产权排序2
ISBN号978-1-4673-7317-3
关键词Blind Source Separation (Bss) Kalman Filter Direction Prediction Component
摘要Deterministic techniques are based on the source-directions and multipath characteristics of the reverberant environment for different source signals. However, searching for the desired directions of the time-block sequence of an acoustic signal is time consuming, and existing deterministic methods rarely consider the motion properties of the acoustic source. In this paper, a real-time acoustic source separation based on a Kalman filter is proposed. First, the convolutive mixture signals captured by the coincident array geometry are formulated, and the basic principles of acoustic source separation based on intensity vector statistics are introduced. Then, a dynamic source-direction prediction method for real-time blind source separation based on a Kalman filter is proposed to predict the directions of a time sequential signal. Finally, extensive experiments are performed with three-source convolutive mixtures of speech in English and Chinese, whose direction varies in linear and nonlinear motions. The signal-to-distortion and signal-to-interference of the separated signals are calculated, and the experimental results demonstrate the feasibility and validity of the proposed method.
语种英语
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文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/17737
专题机器人学研究室
作者单位1.College of Information Science and Engineering, Northeastern University, Shenyang, China
2.State Key Laboratory of Robotics, Shenyang Institute of Automation, CAS, Shenyang, China
推荐引用方式
GB/T 7714
Wei YJ,Wang Y,He YQ. Real-time acoustic source separation based on Kalman filter[C]. Piscataway, NJ, USA:IEEE,2015:1273-1278.
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