2012
DOI: 10.1109/tasl.2011.2166958
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A Speech Distortion and Interference Rejection Constraint Beamformer

Abstract: Abstract-Signals captured by a set of microphones in a speech communication system are mixtures of desired and undesired signals and ambient noise. Existing beamformers can be divided into those that preserve or distort the desired signal. Beamformers that preserve the desired signal are, for example, the linearly constrained minimum variance (LCMV) beamformer that is supposed, ideally, to reject the undesired signal and reduce the ambient noise power, and the minimum variance distortionless response (MVDR) be… Show more

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Cited by 27 publications
(16 citation statements)
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“…A similar relation exists between the conventional LMCP beamformer incorporating interfering speaker suppression constraints and the wLMCP convolutional beamformer in (15). The conventional LCMP beamformer is given by [16] wLCMP =R −1…”
Section: Relation With Conventional Mpdr and Lcmp Beamformersmentioning
confidence: 82%
“…A similar relation exists between the conventional LMCP beamformer incorporating interfering speaker suppression constraints and the wLMCP convolutional beamformer in (15). The conventional LCMP beamformer is given by [16] wLCMP =R −1…”
Section: Relation With Conventional Mpdr and Lcmp Beamformersmentioning
confidence: 82%
“…Various beamformers can be applied after a prior source location has been estimated. We consider, for example, the delay-andsum beamformer [23] due to its simplicity although other forms of beamformers such as presented in [21,32] may be used to enhance the speech signal. The delay-and-sum beamformer output for the prior estimated source location r − k is given as…”
Section: Feature Extractionmentioning
confidence: 99%
“…We consider the delayand-sum beamformer [19] due to its simplicity although other forms of beamformer such as presented in [20,21] can be used to enhance the speech signal. The delay-and-sum beamformer output for the prior estimated source location − k , is given by…”
Section: Feature Extractionmentioning
confidence: 99%