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Adaptive filtering for intelligent sensing speech based on multi-rate LMS algorithm

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Abstract

Adaptive filtering algorithm is one of the most active research topics in signal processing at present. Speech signal processing is the hot issue in the field of digital signal processing. Based on theoretical research of adaptive filter, the work simulated Least mean square error (LMS) adaptive filtering algorithm under different signal-to-noise ratios, spreading to speech signal sequences of different sampling rates. By changing sampling rate factors and filter orders, the work discussed adaptive filtering problems of LMS algorithm under narrowband and broadband interference. Simulation result is consistent with theoretical analysis. With good noise reduction effect, this algorithm is simple and easy to implement.

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Acknowledgements

This work was supported in part by Jiangsu Policy Guidance (Industry University Research) Project (Grant no. BY2016030-16), Major horizontal project (Grant no. KYH15052), Talent Introduction Project (Grant no. KYY15016) and Jiangsu Planned Projects for Postdoctoral Research Funds (Grant no.1601138B).

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Authors and Affiliations

  1. School of Automotive and Traffic Engineering, Jiangsu University of Technology, Changzhou, 213001, Jiangsu, China

    Ranran Liu

  2. Cudatec Development Corp, Changzhou, China

    Ranran Liu

  3. School of Mechanical Engineering, Jiangsu University of Technology, Changzhou, 213001, Jiangsu, China

    Hongxiang Xu & Yifeng Jiang

  4. School of Electrical and Information Engineering, Institute of Bioinformatics and Medical Engineering, Jiangsu University of Technology, Changzhou, China

    Enxing Zheng

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  1. Ranran Liu
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  2. Hongxiang Xu
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  3. Enxing Zheng
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  4. Yifeng Jiang
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Correspondence to Hongxiang Xu.

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Liu, R., Xu, H., Zheng, E. et al. Adaptive filtering for intelligent sensing speech based on multi-rate LMS algorithm. Cluster Comput 20, 1493–1503 (2017). https://doi.org/10.1007/s10586-017-0871-y

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  • DOI: https://doi.org/10.1007/s10586-017-0871-y

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