Searched for: author%3A%22Koutrouvelis%2C+A.%22
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document
Koutrouvelis, A. (author), Hendriks, R.C. (author), Heusdens, R. (author), Jensen, Jesper (author)
The recently proposed relaxed binaural beamforming (RBB) optimization problem provides a flexible tradeoff between noise suppression and binaural-cue preservation of the sound sources in the acoustic scene. It minimizes the output noise power, under the constraints, which guarantee that the target remains unchanged after processing and the...
journal article 2019
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Koutrouvelis, A. (author), Hendriks, R.C. (author), Heusdens, R. (author), Jensen, Jesper (author)
One of the biggest challenges in multimicrophone applications is the estimation of the parameters of the signal model, such as the power spectral densities (PSDs) of the sources, the early (relative) acoustic transfer functions of the sources with respect to the microphones, the PSD of late reverberation, and the PSDs of microphone-self noise...
journal article 2019
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Zhang, J. (author), Koutrouvelis, A. (author), Heusdens, R. (author), Hendriks, R.C. (author)
In this letter, we propose a decentralized framework for rate-distributed linearly constrained minimum variance (LCMV) beamforming in wireless acoustic sensor networks. To save the energy usage within the network, we propose to minimize the transmission cost and put a constraint on the noise reduction performance. Subsequently, we...
journal article 2019
document
Koutrouvelis, A. (author)
The paramount importance of good hearing in everyday life has driven an exploration into the improvement of hearing capabilities of (hearing impaired) people in acoustic challenging situations using hearing assistive devices (HADs). HADs are small portable devices, which primarily aim at improving the intelligibility of an acoustic source that...
doctoral thesis 2018
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Koutrouvelis, A. (author), Sherson, T.W. (author), Heusdens, R. (author), Hendriks, R.C. (author)
We propose a new robust distributed linearly constrained beamformer which utilizes a set of linear equality constraints to reduce the cross power spectral density matrix to a block-diagonal form. The proposed beamformer has a convenient objective function for use in arbitrary distributed network topologies while having identical performance...
journal article 2018
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Koutrouvelis, A. (author), Hendriks, R.C. (author), Heusdens, R. (author), Jensen, Jesper (author)
In this paper, we propose a new binaural beamforming technique, which can be seen as a relaxation of the linearly constrained minimum variance (LCMV) framework. The proposed method can achieve simultaneous noise reduction and exact binaural cue preservation of the target source, similar to the binaural minimum variance distortionless response ...
journal article 2017
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Koutrouvelis, A. (author), Hendriks, R.C. (author), Jensen, J (author), Heusdens, R. (author)
We propose a new multi-microphone noise reduction technique for binaural cue preservation of the desired source and the interferers. This method is based on the linearly constrained minimum variance (LCMV) framework, where the constraints are used for the binaural cue preservation of the desired source and of multiple interferers. In this...
conference paper 2016
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Koutrouvelis, A. (author), Kafentzis, GP (author), Gaubitch, N.D. (author), Heusdens, R. (author)
We propose a fast speech analysis method which simultaneously performs high-resolution voiced/unvoiced detection (VUD) and accurate estimation of glottal closure and glottal opening instants (GCIs and GOIs, respectively). The proposed algorithm exploits the structure of the glottal flow derivative in order to estimate GCIs and GOIs only in...
journal article 2015
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