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dc.contributor.authorYong, Pei Chee
dc.contributor.authorNordholm, Sven
dc.date.accessioned2017-03-15T22:27:20Z
dc.date.available2017-03-15T22:27:20Z
dc.date.created2017-03-14T06:55:57Z
dc.date.issued2016
dc.identifier.citationYong, P.C. and Nordholm, S. 2016. An improved soft decision based noise power estimation employing adaptive prior and conditional smoothing, 15th International Workshop on Acoustic Signal Enhancement (IWAENC), 13-16 Sept. 2016: IEEE.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/50628
dc.identifier.doi10.1109/IWAENC.2016.7602916
dc.description.abstract

In this paper, a new approach is proposed to improve a sigmoid and conditional smoothing-based speech presence probability (SPP) method for noise power spectral density (PSD) estimation. In this approach, the a posteriori speech absence probability (SAP) is adapted with a sigmoid function mapped to the normalised spectral average variance in the consecutive frames that can effectively characterise noise variation. The adaptation is also employed in the conditional smoothing stage to characterise the a posteriori SPP, which is then utilised in the noise PSD estimation. Comparison with state of the art methods validates the effectiveness of the proposed method.

dc.titleAn improved soft decision based noise power estimation employing adaptive prior and conditional smoothing
dc.typeConference Paper
dcterms.source.title2016 International Workshop on Acoustic Signal Enhancement (IWAENC)
dcterms.source.series2016 International Workshop on Acoustic Signal Enhancement, IWAENC 2016
dcterms.source.isbn9781509020072
dcterms.source.conference15th International Workshop on Acoustic Signal Enhancement (IWAENC)
curtin.departmentSchool of Electrical Engineering and Computing
curtin.accessStatusFulltext not available


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