Dual-channel noise reduction based on a mixture of circular-symmetric complex Gaussians on unit hypersphere
2013 (English)In: ICASSP IEEE Int Conf Acoust Speech Signal Process Proc, 2013, 7289-7293 p.Conference paper (Refereed)
In this paper a model-based dual-channel noise reduction approach is presented which is an alternative to conventional noise reduction algorithms essentially due to its independence of the noise power spectral density estimation and of any prior knowledge about the spatial noise field characteristics. We use a mixture of circular-symmetric complex-Gaussian distributions projected on the unit hypersphere for modeling the complex discrete Fourier transform coefficients of noisy speech signals in the frequency domain. According to the derived mixture model, clustering of the noise and the target speech components is performed depending on their direction of arrival. A soft masking strategy is proposed for speech enhancement based on responsibilities assigned to the target speech class in each time-frequency bin. Our experimental results show that the proposed approach is more robust than conventional dual-channel noise reduction systems based on the single- and dual-channel noise power spectral density estimators.
Place, publisher, year, edition, pages
2013. 7289-7293 p.
, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, ISSN 1520-6149
dual-channel noise reduction, mixture of Gaussians, soft masking, Speech enhancement
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:kth:diva-140044DOI: 10.1109/ICASSP.2013.6639078ScopusID: 2-s2.0-84890523358ISBN: 9781479903566OAI: oai:DiVA.org:kth-140044DiVA: diva2:689452
2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013, 26 May 2013 through 31 May 2013, Vancouver, BC
QC 201401202014-01-202014-01-162014-01-20Bibliographically approved