access icon free Acoustic echo cancellation by minimising mutual information within sliding DFT window

An acoustic echo cancellation (AEC) algorithm based on minimising the mutual information between the loudspeaker and system output signals over a sliding discrete Fourier transform (DFT) window, for single AEC parameter estimation, is introduced. Unlike the conventional least-mean-square (LMS) systems, the proposed algorithm requires no double-talk detection (DTD) and its AEC parameter can be continually updated. Although it has been shown that independent component analysis (ICA) allows continual adaptation of the AEC parameters under DTD, current ICA-based algorithms estimate a filter of the same length as that of the LMS techniques. The sliding DFT window is utilised to facilitate adaptation of only one AEC parameter for deflation of the far-end signal, thereby greatly reducing the computational load.

Inspec keywords: parameter estimation; acoustic signal processing; least mean squares methods; independent component analysis; discrete Fourier transforms; echo suppression; loudspeakers

Other keywords: DTD; acoustic echo cancellation; mutual information; sliding DFT window; ICA; independent component analysis; sliding discrete Fourier transform; loudspeaker; least mean squares systems; parameter estimation; double talk detection

Subjects: Electromagnetic compatibility and interference; Numerical approximation and analysis; Signal processing and detection; Integral transforms in numerical analysis; Probability theory, stochastic processes, and statistics; Acoustic signal processing; Other topics in statistics

References

    1. 1)
      • 1. Hänsler, E., Schmidt, G.: ‘Topics in acoustic echo and noise control’ (Springer, New York, 2006).
    2. 2)
      • 3. Yang, J.-M., Sakai, H.: ‘A robust ICA-based adaptive filter algorithm for system identification’, IEEE Trans. Circuits Syst., 2008, 55, pp. 12591263 (doi: 10.1109/TCSII.2008.2008060).
    3. 3)
      • 4. Zhang, G., Li, J., Li, C.: ‘A novel blind deconvolution algorithm using single frequency bin’, J. Zhejiang Univ. Sci. A, 2007, 8, pp. 12711276 (doi: 10.1631/jzus.2007.A1271).
    4. 4)
      • 5. Babaie-Zadeh, M., Jutten, C.: ‘Differential of mutual information’, IEEE Signal Process. Lett., 2004, 11, pp. 4851 (doi: 10.1109/LSP.2003.819344).
    5. 5)
      • 2. Park, Y.-H., Park, H.-M.: ‘DTD-free nonlinear acoustic echo cancellation based on independent component analysis’, Electron. Lett., 2010, 46, pp. 866868 (doi: 10.1049/el.2010.0848).
http://iet.metastore.ingenta.com/content/journals/10.1049/el.2013.3053
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