Title
Independent Vector Analysis Assisted Adaptive Beamfomring for Speech Source Separation with an Acoustic Vector Sensor
Abstract
Acoustic vector sensor (AVS), as a compact sensor with the capability of forming a frequency-invariant spatial beampattern over the 3D space, has potential in source separation. A straightforward way to achieve source separation with AVS is through adaptive beamforming. Such a method requires the direction-of-arrival (DOA) information, which is challenging to estimate accurately in reverberant environments. To circumvent this issue, we present a framework jointly implementing adaptive beamforming and independent vector analysis (IVA). Different from the conventional beamforming, the presented method only require rough DOA estimation for initialization. It iteratively refines the estimates of source DOA and signal statistics. The proposed method has great advantages of improving source separation performance and enhancing DOA estimation accuracy. Simulations demonstrate the properties of the developed method.
Year
DOI
Venue
2022
10.1109/IWAENC53105.2022.9914741
2022 International Workshop on Acoustic Signal Enhancement (IWAENC)
Keywords
DocType
ISBN
Adaptive beamforming,independent vector analysis,acoustic vector sensor
Conference
978-1-6654-6868-8
Citations 
PageRank 
References 
0
0.34
19
Authors
4
Name
Order
Citations
PageRank
Yichen Yang100.34
Xianrui Wang200.34
Wen Zhang300.34
Jingdong Chen41460128.79