06-05-2014, 02:53 PM
ACOUSTIC ECHO CANCELLATION ALGORITHM TOLERABLE FOR DOUBLE TALK
ECHO CANCELLATION.doc (Size: 30 KB / Downloads: 25)
INTRODUCTION:
In acoustic echo cancellation (AEC) applications, where the acoustic echo paths are extremely long, the adaptive filter works most likely in an under-modeling situation. Acoustic echo cancellation (AEC) is one of the most popular applications of adaptive filtering. In acoustic echo canceller’s systems, the coefficients of adaptive filter are disturbed by two factors. One is the power fluctuation of far end talker’s signal used for estimating the coefficients. This disturbance, however, can be easily prevented by applying the block length control to the estimation. An other is the superposition of near end talker’s signal on the acoustic echo, called double talk. This means that the exact and quick detection of the superposition is requisite to the prevention.
METHODOLOGY:
This project proposes a step size control method capable of steadily canceling acoustic echo resisting double talk. The method is characterized by applying a sub-adaptive filter to the control. The step size and the number of taps of the sub- adaptive filter are larger and fewer than those of the main adaptive filter used for canceling the acoustic echo, respectively. Accordingly, the sub-adaptive filter can reduce the residual echo more rapidly than the main adaptive filter. The proposed method applies the step size calculated using the residual echo to the main adaptive filter, and thereby, quickly and steadily reduces the acoustic echo. This project finally verifies that the proposed method can provide almost the same convergence speed as that obtained by applying a fixed large step size to the main adaptive filter.
BACKGROUND:
The superposition of near end talker’s signal on the acoustic echo, called double talk. Several methods are proposed that are capable of steadily estimating the coefficients with out passing the estimation even during the double talk. The methods however have the drawback that the convergence speed of the coefficients is extremely slow while the estimation error is large. In the new method, the variable step size given to the main adaptive filter canceling the acoustic echo is adjusted using the residual echo provided by another adaptive filter, called sub-adaptive filter. The fixed step size and number of taps of the sub-adaptive filter are larger and fewer than those of the main adaptive filter. The variable step size thereby increases quickly; consequently, the main adaptive filter can swiftly reduce the acoustic echo. The project also verifies that the proposed method can provide almost the same convergence speed as that obtained by applying a fixed large step size to the main adaptive filter.