A Multidelay Double-Talk Detector Combined with the MDF Adaptive Filter
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A Multidelay Double-Talk Detector Combined with the MDF Adaptive Filter Jacob Benesty Universit´e du Qu´ebec, INRS-EMT 800 de la Gaucheti`ere Ouest, Suite 6900 Montr´eal, Qu´ebec, Canada H5A 1K6 Email: [email protected]
¨ Tomas Gansler Agere Systems, 555 Union Boulevard, Allentown, PA 18109-3229, USA Email: [email protected] Received 31 July 2002 and in revised form 5 March 2003 The multidelay block frequency-domain (MDF) adaptive filter is an excellent candidate for both acoustic and network echo cancellation. There is a need for a very good double-talk detector (DTD) to be combined efficiently with the MDF algorithm. Recently, a DTD based on a normalized cross-correlation vector was proposed and it was shown that this DTD performs much better than the Geigel algorithm and other DTDs based on the cross-correlation coefficient. In this paper, we show how to extend the definition of a normalized cross-correlation vector in the frequency domain for the general case where the block size of the Fourier transform is smaller than the length of the adaptive filter. The resulting DTD has an MDF structure, which makes it easy to implement, and a good fit with an echo canceler based on the MDF algorithm. We also analyze resource requirements (computational complexity and memory requirement) and compare the MDF algorithm with the normalized least mean square algorithm (NLMS) from this point of view. Keywords and phrases: adaptive filtering, frequency domain, double-talk detection, echo cancellation.
1.
INTRODUCTION
Network and acoustic echo cancelers work on the same principle. An echo canceler (EC) [1], to work well, should include good solutions to two important problems: a system identification problem and a so-called double-talk detection problem [2]. When the echo path is identified by an adaptive filter, a function should be included to freeze the adaptation whenever a near-end signal is detected, and thereby avoid the divergence of the adaptive algorithm. This control can either be done by a so-called step-size control (soft decision) or by a double-talk detector (DTD) hard decision. Theoretically, the step-size control method would be preferable because it can be made optimal in minimum mean-square sense [3, 4, 5]. In practice however, depending on situation, there is no conclusive evidence that soft decisions (step-size control) result in better performance than using the DTD hard decisions. Hence, it is of great interest to find a suitable and practical decision variable. One of the most widely used DTDs is the Geigel algorithm [6] which works fairly well when the echo return loss is well defined. However, this is not, in general, the case in practice. The need for more sophisticated DTDs that do not depend on the path attenuation is obvious. Alternative
methods for double-talk detection have been presented, for example, in [7, 8]. A family of DTDs exhibiting this feature was proposed in [9]. On the system identification part, the multidelay block frequency-domain (MDF) adaptive filter [10] is an excellent
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