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[Keyword] step size control(2hit)

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  • A Step Size Control Method Improving Estimation Speed in Double Talk Term

    Takuto YOSHIOKA  Kana YAMASAKI  Takuya SAWADA  Kensaku FUJII  Mitsuji MUNEYASU  Masakazu MORIMOTO  

     
    PAPER-Digital Signal Processing

      Vol:
    E96-A No:7
      Page(s):
    1543-1551

    In this paper, we propose a step size control method capable of quickly canceling acoustic echo even when double talk continues from the echo path change. This method controls the step size by substituting the norm of the difference vector between the coefficient vectors of a main adaptive filter (Main-ADF) and a sub-adaptive filter (Sub-ADF) for the estimation error provided by the former. Actually, the number of taps of Sub-ADF is limited to a quarter of that of Main-ADF, and the larger step size than that applied to Main-ADF is given to Sub-ADF; accordingly the norm of the difference vector quickly approximates to the estimation error. The estimation speed can be improved by utilizing the norm of the difference vector for the step size control in Main-ADF. We show using speech signals that in single talk the proposed method can provide almost the same estimation speed as the method whose step size is fixed at the optimum one and verify that even in double talk the estimation error, quickly decreases.

  • Acoustic Echo Cancellation Using Sub-Adaptive Filter

    Satoshi OHTA  Yoshinobu KAJIKAWA  Yasuo NOMURA  

     
    PAPER-Digital Signal Processing

      Vol:
    E91-A No:4
      Page(s):
    1155-1161

    In the acoustic echo canceller (AEC), the step-size parameter of the adaptive filter must be varied according to the situation if double talk occurs and/or the echo path changes. We propose an AEC that uses a sub-adaptive filter. The proposed AEC can control the step-size parameter according to the situation. Moreover, it offers superior convergence compared to the conventional AEC even when the double talk and the echo path change occur simultaneously. Simulations demonstrate that the proposed AEC can achieve higher ERLE and faster convergence than the conventional AEC. The computational complexity of the proposed AEC can be reduced by reducing the number of taps of the sub-adaptive filter.

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