Car Noise Suppression Using Adaptive Noise Canceller with Speech Suppressors

2016 ◽  
Vol 136 (8) ◽  
pp. 1218-1229
Author(s):  
Yuya Honda ◽  
Arata Kawamura ◽  
Youji Iiguni
2013 ◽  
Vol 811 ◽  
pp. 375-379
Author(s):  
Jing Mo ◽  
Wei He ◽  
Ruo Yan Han ◽  
Jing Wei Wu ◽  
Dan Su

A variable step long LMS algorithm based on Bessel function was put forward, which established the functional relationship between the step size factor and the error signal. And this algorithm would be applied to the adaptive noise canceller in order to improve the ability of the algorithm of uncorrelated noise suppression. This algorithm has a larger step-size during initial convergence stage or unknown system parameters change in order to get a faster convergence time and tracking speed. Moreover, and it adjusts small step-size to achieve a very small steady-state maladjustment noise after the convergence of the algorithm.


Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1878
Author(s):  
Yi Zhou ◽  
Haiping Wang ◽  
Yijing Chu ◽  
Hongqing Liu

The use of multiple spatially distributed microphones allows performing spatial filtering along with conventional temporal filtering, which can better reject the interference signals, leading to an overall improvement of the speech quality. In this paper, we propose a novel dual-microphone generalized sidelobe canceller (GSC) algorithm assisted by a bone-conduction (BC) sensor for speech enhancement, which is named BC-assisted GSC (BCA-GSC) algorithm. The BC sensor is relatively insensitive to the ambient noise compared to the conventional air-conduction (AC) microphone. Hence, BC speech can be analyzed to generate very accurate voice activity detection (VAD), even in a high noise environment. The proposed algorithm incorporates the VAD information obtained by the BC speech into the adaptive blocking matrix (ABM) and adaptive noise canceller (ANC) in GSC. By using VAD to control ABM and combining VAD with signal-to-interference ratio (SIR) to control ANC, the proposed method could suppress interferences and improve the overall performance of GSC significantly. It is verified by experiments that the proposed GSC system not only improves speech quality remarkably but also boosts speech intelligibility.


2021 ◽  
Vol 11 (6) ◽  
pp. 2816
Author(s):  
Hansol Kim ◽  
Jong Won Shin

The transfer function-generalized sidelobe canceller (TF-GSC) is one of the most popular structures for the adaptive beamformer used in multi-channel speech enhancement. Although the TF-GSC has shown decent performance, a certain amount of steering error is inevitable, which causes leakage of speech components through the blocking matrix (BM) and distortion in the fixed beamformer (FBF) output. In this paper, we propose to suppress the leaked signal in the output of the BM and restore the desired signal in the FBF output of the TF-GSC. To reduce the risk of attenuating speech in the adaptive noise canceller (ANC), the speech component in the output of the BM is suppressed by applying a gain function similar to the square-root Wiener filter, assuming that a certain portion of the desired speech should be leaked into the BM output. Additionally, we propose to restore the attenuated desired signal in the FBF output by adding some of the microphone signal components back, depending on how microphone signals are related to the FBF and BM outputs. The experimental results showed that the proposed TF-GSC outperformed conventional TF-GSC in terms of the perceptual evaluation of speech quality (PESQ) scores under various noise conditions and the direction of arrivals for the desired and interfering sources.


2015 ◽  
Vol 7 (2) ◽  
pp. 45-58 ◽  
Author(s):  
Farhana Afroz ◽  
Asadul Huq ◽  
Ahmed F ◽  
Kumbesan Sandrasegaran

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