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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Autoren:
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)

Inhalt:
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.