A generalized estimation approach for linear and nonlinear microphone array post-filters

Lefkimmiatis, Stamatios; Maragos, Petros

doi:10.1016/j.specom.2007.02.004

Cited by 41 publications

(38 citation statements)

References 24 publications

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“…Since the focus of our evaluation is the CDR estimation, we apply the suppression simply to the first microphone signal. Alternatives would be to average the power spectra between microphones [4], or to use beamforming to combine the signals, which would however change the CDR and therefore require consideration in the suppression filter computation [19]. • .…”

Section: Cdr-based Dereverberationmentioning

confidence: 99%

Unbiased coherent-to-diffuse ratio estimation for dereverberation

Schwarz

Kellermann

2014

2014 14th International Workshop on Acoustic Signal Enhancement (IWAENC)

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We investigate the estimation of the time-and frequencydependent coherent-to-diffuse ratio (CDR) from the measured spatial coherence between two omnidirectional microphones. We illustrate the relationship between several known CDR estimators using a geometric interpretation in the complex plane, discuss the problem of estimator bias, and propose unbiased versions of the estimators. Furthermore, we show that knowledge of either the direction of arrival (DOA) of the target source or the coherence of the noise field is sufficient for an unbiased CDR estimation. Finally, we apply the CDR estimators to the problem of dereverberation, using automatic speech recognition word error rate as objective performance measure.

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Section: Cdr-based Dereverberationmentioning

confidence: 99%

Unbiased coherent-to-diffuse ratio estimation for dereverberation

Schwarz

Kellermann

2014

2014 14th International Workshop on Acoustic Signal Enhancement (IWAENC)

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“…The MVDR beamformer weights and the post-filter transfer function for each of the MMSE, STSA and log-STSA post-filters are estimated using the estimation procedure proposed in [14].…”

Section: A Multichannel Speech Enhancement Systemmentioning

confidence: 99%

Experiments on far-field multichannel speech processing in smart homes

Rodomagoulakis

Giannoulis

Skordilis

et al. 2013

2013 18th International Conference on Digital Signal Processing (DSP)

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Abstract-In this paper, we examine three problems that rise in the modern, challenging area of far-field speech processing. The developed methods for each problem, namely (a) multichannel speech enhancement, (b) voice activity detection, and (c) speech recognition, are potentially applicable to a distant speech recognition system for voice-enabled smart home environments. The obtained results on real and simulated data, regarding the smart home speech applications, are quite promising due to the accomplished improvements made in the employed signal processing methods.

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“…However, both methods overestimate the noise power spectral density at the beamformer's output and, thus, they are suboptimal in the Wiener sense (Simmer & Wasiljeff, 1992). In (Lefkimmiatis & Maragos, 2007), the authors have obtained a more accurate estimation of the noise power spectral density at the output of the beamformer proposed in (Simmer & Wasiljeff, 1992) by taking into account the noise reduction performed by the minimum variance distortionless response (MVDR) beamformer.…”

Section: State Of the Artmentioning

confidence: 99%