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Noise Power Estimation Based on the Probability of Speech Presence
KTH, School of Electrical Engineering (EES). (Sound and Image Processing Lab)
Delft University of Technology. (Signal and Information Processing Lab)
2011 (English)In: Proceedings IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2011, 145-148 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we analyze the minimum mean square error (MMSE) based spectral noise power estimator [1] and present an improve-ment. We will show that the MMSE based spectral noise powerestimate is only updated when the a posteriori signal-to-noise ratio (SNR) is lower than one. This threshold on the a posteriori SNRcan be interpreted as a voice activity detector (VAD).We propose in this work to replace the hard decision of theVAD by a soft speech presence probability (SPP). We show thatby doing so, the proposed estimator does not require a bias cor-rection and safety-net as is required by the MMSE estimator pre-sented in [1]. At the same time, the proposed estimator maintainsthe quick noise tracking capability which is characteristic for theMMSE noise tracker, results in less noise power overestimation andis computationally less expensive.

Place, publisher, year, edition, pages
2011. 145-148 p.
National Category
Signal Processing
Research subject
SRA - ICT
Identifiers
URN: urn:nbn:se:kth:diva-42717ISI: 000298302900037Scopus ID: 2-s2.0-83455170765OAI: oai:DiVA.org:kth-42717DiVA: diva2:447538
Conference
IEEE Workshop on Applications of Signal Processing to Audio and Acoustics
Note
QC 20111014Available from: 2011-10-12 Created: 2011-10-12 Last updated: 2012-04-03Bibliographically approved

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