Car Noise Suppression Using Adaptive Noise Canceller with Speech Suppressors

Yuya Honda; Arata Kawamura; Youji Iiguni

doi:10.1541/ieejeiss.136.1218

A Variable-Step LMS Algorithm Based on the Adaptive Noise Cancellation

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.811.375 ◽

2013 ◽

Vol 811 ◽

pp. 375-379

Author(s):

Jing Mo ◽

Wei He ◽

Ruo Yan Han ◽

Jing Wei Wu ◽

Dan Su

Keyword(s):

Noise Suppression ◽

Lms Algorithm ◽

Convergence Time ◽

Size Factor ◽

Adaptive Noise Cancellation ◽

Step Size ◽

Variable Step ◽

Unknown System ◽

Adaptive Noise ◽

Adaptive Noise Canceller

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.

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A Robust Dual-Microphone Generalized Sidelobe Canceller Using a Bone-Conduction Sensor for Speech Enhancement

Sensors ◽

10.3390/s21051878 ◽

2021 ◽

Vol 21 (5) ◽

pp. 1878

Author(s):

Yi Zhou ◽

Haiping Wang ◽

Yijing Chu ◽

Hongqing Liu

Keyword(s):

Speech Enhancement ◽

Speech Intelligibility ◽

Bone Conduction ◽

Speech Quality ◽

Generalized Sidelobe Canceller ◽

Spatially Distributed ◽

Interference Signals ◽

Adaptive Noise ◽

Adaptive Noise Canceller ◽

Sidelobe Canceller

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.

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Dual-Mic Speech Enhancement Based on TF-GSC with Leakage Suppression and Signal Recovery

Applied Sciences ◽

10.3390/app11062816 ◽

2021 ◽

Vol 11 (6) ◽

pp. 2816

Author(s):

Hansol Kim ◽

Jong Won Shin

Keyword(s):

Speech Enhancement ◽

Wiener Filter ◽

Signal Recovery ◽

Gain Function ◽

Microphone Signal ◽

Perceptual Evaluation ◽

Blocking Matrix ◽

Adaptive Noise ◽

Adaptive Noise Canceller ◽

Sidelobe Canceller

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.

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