Download PDF by Atanasov D.V.: 5th International Conference on Geometry and Applications

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Chapter 9 uses multichannel linear prediction to derive an equalization filter without necessarily estimating the acoustic impulse responses first. This equalization filter results in excessive whitening of the speech and, consequently, four different methods to overcome this problem are presented. Chapter 10 presents TRINICON – a generic framework for Multi-Input MultiOutput (MIMO) signal processing. It is applied here to derive two dereverberation algorithms: one where the AIRs are first identified blindly and used to design equalization filters, and the second where the equalization filters are identified directly from the reverberant observations.

New Paltz, NY (2007) 87. : Source waveform recovery in a reverberant space by cepstrum dereverberation. In: Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), vol. 1, pp. 157–160 (1993) 88. : Delay-and-predict equalization for blind speech dereverberation. In: Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP). Toulouse, France (2006) 89. : Beamforming: a versatile approach to spatial filtering. IEEE Signal Process. Mag. 5(2), 4–24 (1988) 90. : Sound and rock art.

EVAM: An eigenvector-based algorithm for multichannel blind deconvolution of input colored signals. IEEE Trans. Signal Process. 43(1), 143–149 (1995) 37. : The influence of a single echo on the audibility of speech. J. Audio Eng. Soc. 20, 145–159 (1972) 38. : Multi-channel speech dereverberation based on a statistical model of late reverberation. In: Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), vol. 4, pp. iv/173–iv/176. Philadelphia (2005) 39. : Single- and multi-microphone speech dereverberation using spectral enhancement.

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5th International Conference on Geometry and Applications by Atanasov D.V.


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