Adaptive combination of subband adaptive filters with selective partial updates
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part I
International Journal of Speech Technology
| Hi-index | 0.43 |
In hands-free telephones and teleconferencing systems, acoustic echo cancellers are required, which are often implemented by adaptive filters. In these applications, the speech input signal of the adaptive filter is highly correlated and the impulse response of the echo path is very long. These characteristics will slow down the convergence rate of the adaptive filter if the well-known normalized least-mean-square (NLMS) algorithm is used. The normalized subband adaptive filter (NSAF) offers a good solution to this problem because of its decorrelating property. However, similar to the NLMS-based adaptive filter, the NSAF requires a tradeoff between fast convergence rate and small steady-state mean-square error (MSE). In this paper, we propose an adaptive combination scheme to address this tradeoff. The combination is carried out in subband domain and the mixing parameter that controls the combination is adapted by means of a stochastic gradient algorithm which employs the sum of squared subband errors as the cost function. The performance of the proposed combination scheme is evaluated in the context of acoustic echo cancellation (AEC). Experimental results show that the combination scheme can obtain both fast convergence rate and small steady-state MSE.