Performance Prediction of the BinauralMVDR Beamformer with Partial Noise Estimation using a Binaural Speech IntelligibilityModel

Konferenz: Speech Communication - 13. ITG-Fachtagung Sprachkommunikation
10.10.2018 - 12.10.2018 in Oldenburg, Deutschland

Tagungsband: ITG-Fb. 282: Speech Communication

Seiten: 5Sprache: EnglischTyp: PDF

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Hauth, Christopher F.; Brand, Thomas (Medizinische Physik and Cluster of Excellence Hearing4All, University of Oldenburg, Oldenburg, Germany)
Goessling, Nico (University of Oldenburg, Department of Medical Physics and Cluster of Excellence Hearing4All, Oldenburg, Germany)

An objective evaluation of binaural noise reduction algorithms allows for directly comparing the performance of different algorithm realizations. Here, a binaural speech intelligibility model (BSIM), which mimics the effective binaural processing of a human listeners, is used to predict the performance of the binaural minimum-variance distortionless response beamformer with partial noise estimation (BMVDR-N), which aims at preserving the speech component in a reference microphone and a scaled version of the noise component. The BMVDR-N beamformer is evaluated with respect to a predicted change in SRT depending on the parameter η, which controls a trade-off between noise reduction and binaural cue preservation of the noise component. The results show that BSIM benefits from the preserved binaural cues suggesting that the BMVDR-N beamformer can improve the spatial quality of a scene without affecting speech intelligibility.