Geometrically Constrained TRINICON-based relative transfer function estimation in underdetermined scenarios

Reindl, Klaus; Markovich‐Golan, Shmulik; Barfuss, Hendrik; Gannot, Sharon; Kellermann, Walter

doi:10.1109/waspaa.2013.6701822

Cited by 27 publications

(19 citation statements)

References 7 publications

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“…However, even in such complex scenarios, Directional BSS can produce an acceptable estimate of the RTF without any source activity detection. In the latest work [53], more evaluation results for comparing the estimated RTFs with the true RTFs are shown. The performance of Directional BSS is somewhat dependent on the signal characteristics (stationary or nonstationary, speech signal or white noise) of the involved sources.…”

Section: Target Suppression Performancementioning

confidence: 99%

“…Conventionally, it can be used for a realization which relies on a noise estimate produced by an RTF-based BM [25,53] or for the MWF which requires an SOS estimate of the noise [54]. In this section, we discuss one generic application to show the effectiveness of the noise estimation of the proposed BM.…”

Section: A Two-unit Scheme: Bm Plus Spectral Enhancement Filtersmentioning

confidence: 99%

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Analysis of dual-channel ICA-based blocking matrix for improved noise estimation

Zheng

Reindl

Kellermann

2014

EURASIP J. Adv. Signal Process.

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For speech enhancement or blind signal extraction (BSE), estimating interference and noise characteristics is decisive for its performance. For multichannel approaches using multiple microphone signals, a BSE scheme combining a blocking matrix (BM) and spectral enhancement filters was proposed in numerous publications. For such schemes, the BM provides a noise estimate by suppressing the target signal only. The estimated noise reference is then used to design spectral enhancement filters for the purpose of noise reduction. For designing the BM, 'Directional Blind Source Separation (BSS)' was already proposed earlier. This method combines a generic BSS algorithm with a geometric constraint derived from prior information on the target source position to obtain an estimate for all interfering point sources and diffuse background noise. In this paper, we provide a theoretical analysis to show that Directional BSS converges to a relative transfer function (RTF)-based BM. The behavior of this informed signal separation scheme is analyzed and the blocking performance of Directional BSS under various acoustical conditions is evaluated. The robustness of Directional BSS regarding the localization error for the target source position is verified by experiments. Finally, a BSE scheme combining Directional BSS and Wiener-type spectral enhancement filters is described and evaluated.

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Section: Target Suppression Performancementioning

confidence: 99%

Section: A Two-unit Scheme: Bm Plus Spectral Enhancement Filtersmentioning

confidence: 99%

Analysis of dual-channel ICA-based blocking matrix for improved noise estimation

Zheng

Reindl

Kellermann

2014

EURASIP J. Adv. Signal Process.

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“…Apparatus such as the minimum variance distortionless response (MVDR) beamformer [4], [5], the linearly-constrained minimum variance (LCMV) beamformer [6], [7], the speech-distortion weighted multi-channel Wiener (SDW-MWF) filter [8]- [10], the transfer function generalized sidelobe canceler (TF-GLC) [11]- [14], and alike, can be used for distributed microphone arrays; however, the dominant trend is to implement these algorithms in a centralized approach. The centralized approach is not useful in ad hoc arrays for its huge communication and computational overheads.…”

Section: Introductionmentioning

confidence: 99%

Ad hoc microphone array beamforming using the primal-dual method of multipliers

Tavakoli

Jensen

Heusdens

et al. 2016

2016 24th European Signal Processing Conference (EUSIPCO)

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Abstract-In the recent years, there have been an increasing amount of researches aiming at optimal beamforming with ad hoc microphone arrays, mostly fusion-center-based schemes. However, huge computational complexities and communication overheads impede many of these algorithms from being useful in practice. In this paper, we propose a low-footprint optimization approach to reduce the convergence time and overheads for the distributed beamforming problem. We transcribe the pseudocoherence-based beamforming which is insightful for taking into account the nature of speech. We formulate the distributed minimum variance distortionless response beamformer using the primal-dual method of multipliers. Our experiments confirm the fast convergence using the proposed distributed algorithm. It is also shown how a hard limit on the number of iterations affects the performance of the array in noise and interference suppression.Index Terms-Speech enhancement, ad hoc microphone array, distributed beamforming, primal-dual method of multipliers.

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“…The challenge is to compute or update the filters when directional and non-stationary noise is present. Blind methods can be used [9,10], however, since h L and h R are typically long and dense, the statistical error due to blind estimation may radically deteriorate the efficiency of the estimated CF. Recent efforts have therefore been made to lower the dimensionality of that problem using prior knowledge [11,20,25].…”

Section: Introductionmentioning

confidence: 99%

Sparse target cancellation filters with application to semi-blind noise extraction

Málek

Koldovsky

2014

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Impulse responses of filters that perform spatial null in a target direction, so-called target-cancellation filters (CFs), are usually long and dense due to the reverberant acoustic environment. It is therefore hard to blindly estimate them from noisy recordings of the target. In this paper, we show that efficient sparse CFs having many coefficients equal to zero can be designed such that their cancellation performance is tolerably lower than the performance of dense CFs. We show that an efficient sparse CF can be blindly estimated from noisy data, provided that its support is known. The resulting filter is better than a dense CF which has been blindly estimated without any prior knowledge.

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Geometrically Constrained TRINICON-based relative transfer function estimation in underdetermined scenarios

Cited by 27 publications

References 7 publications

Analysis of dual-channel ICA-based blocking matrix for improved noise estimation

Analysis of dual-channel ICA-based blocking matrix for improved noise estimation

Ad hoc microphone array beamforming using the primal-dual method of multipliers

Sparse target cancellation filters with application to semi-blind noise extraction

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