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Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181
DOI: 10.1109/icassp.1998.679682
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Using auditory properties to improve the behaviour of stereophonic acoustic echo cancellers

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Cited by 48 publications
(45 citation statements)
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“…To realistic TV conferencing, multi-channel audio, at least stereophonic, is essential. For stereophonic teleconferencing, stereophonic acoustic echo cancellers have been studied [1][2][3][4][5][6][7][8][9].…”
Section: Introductionmentioning
confidence: 99%
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“…To realistic TV conferencing, multi-channel audio, at least stereophonic, is essential. For stereophonic teleconferencing, stereophonic acoustic echo cancellers have been studied [1][2][3][4][5][6][7][8][9].…”
Section: Introductionmentioning
confidence: 99%
“…Strong crosscorrelation between input signals causes incorrect identification of the echo paths. To overcome this problem, improved echo cancellation algorithms have been proposed [5][6][7][8][9]. Some of these algorithms introduce a pre-processing which artificially varies the cross-correlation [5,6].…”
Section: Introductionmentioning
confidence: 99%
“…As a consequence of this, suitable multichannel AEC algorithms have been developed to deal with the echo problem in presence of multiple audio paths, where the task to be solved is tougher than in the single-channel case study, as rigorously illustrated in [2]. Indeed, the "non-uniqueness problem" occurs in the multichannel scenario, due to the high correlation degree between recorded signals: a very popular involved technique involves the addition of a decorrelation module to allow multichannel adaptive filtering working properly [2][3][4][5].…”
Section: Introductionmentioning
confidence: 99%
“…H. Khong misalignment problem in this practical case, several approaches have been employed to decorrelate the two input signals using, for example, nonlinear processing [4]- [6], spectrally shaped random noise [7], [8], comb filtering [9], leaky extended LMS [10], and alternating fixed-point [11] algorithms. The common aim of these algorithms is to achieve decorrelation of input signals and without affecting the quality or stereophonic image of the speech.…”
mentioning
confidence: 99%