Audio Signal Detection and Enhancement Based on Linear CMOS Array and Multi-Channel Data Fusion

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ID: 113919
2020
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Abstract
An audio signal detection system based on laser speckle and multi-channel data fusion is presented. A linear CMOS array is used as the detector, which owns a fast line rate and suitable sensing size. The signals from the pixels are selected and fused to enhance the reconstructed signal. The reconstructed audio signals are evaluated with a segmental SNR (SegSNR) algorithm. The experimental results of three categories of audio sources (single voice audio, conversation and music) show that data fusion can improve the SegSNR scores. Especially, direct phase-error based filtering (pbf) fusion gives a nearly 3.0 dB increase and obtains another 1.0 dB increase with the combination of single channel process. The experimental results show that the fusion algorithms are not sensitive to audio types and the performance of multi-channel data fusion is not weakened with the increase of measuring distance. This feature has potential applications in remote sensing. The intelligibility of the fused audio signals is evaluated with normalized subband envelope correlation (NSEC) algorithm and the evaluation results shows that fusion can also enhance the intelligibility of the recovered signal.
Reference Key
sun2020ieeeaudio Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Cong Dai,Chang Liu,Yanfang Wu,Xiaozhong Wang,Hongyan Fu,Haixin Sun;Cong Dai;Chang Liu;Yanfang Wu;Xiaozhong Wang;Hongyan Fu;Haixin Sun;
Journal ieee access
Year 2020
DOI
10.1109/access.2020.3010325
URL
https://sciprofiles.com/publication/view/dd90ab46cfbf7e21865d3e1341303a19
Keywords
data integration signal processing algorithms vibrations signal to noise ratio speckle laser beams

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