Paper Info
Title
Exploiting The Directional Coherence Function For Multichannel Source Extraction
Abstract
The desired speech detector plays an important role for controlling the speech distortion in spatial filtering based speech enhancement algorithms. However, the conventional complex coherence(CC) based algorithms can only distinguish the coherent speech and diffuse noise. To improve the performance on the scenarios that both the coherent interference and diffuse noise are present, we propose a directional coherence function(DCF) based detector in this paper. Based on a pair of complementary filters which can suppress the diffuse noise and the coherent interference respectively, the DCF is computed as the normalized correlation between the filters? outputs. Meanwhile, the filters are solved by convex programming method and satisfy the constraints on speech distortionless and white noise gain(WNG). Consequently, the value of DCF will be close to 1 only for the desired speech dominated time-frequency(T-F) bins and much smaller than 1 for the noise or interference dominated T-F bins. To extract the desired speech, the DCF based Desired Speech Presence Probability(DSPP) is used to control the adaptation in general sidelobe canceler(GSC), and subsequently used as the post-filtering weight. Systematical experiments on several scenarios show that the proposed algorithm achieves significantly and consistently better noise suppression performance than the narrowband direction-of-arrival(DOA) estimates based algorithms.
Year
DOI
Venue
2021
10.1016/j.specom.2021.01.002
SPEECH COMMUNICATION
Keywords
DocType
Volume
Directional coherence function, Coherent-to-Diffuse Ratio, General sidelobe canceller, Desired Speech Presence Probability
Journal
128
ISSN
Citations 
PageRank 
0167-6393
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Shan Liang1208.52
Guanjun Li252.46
Shuai Nie3408.30
Zhanlei Yang4317.77
Wenju Liu521439.32
Jianhua Tao6848138.00