Single channel speech enhancement using Bayesian NMF with recursive temporal updates of prior distributions
2012 (English)In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012, IEEE conference proceedings, 2012, 4561-4564 p.Conference paper (Refereed)
We present a speech enhancement algorithm which is based on a Bayesian Nonnegative Matrix Factorization (NMF). Both Minimum Mean Square Error (MMSE) and Maximum a-Posteriori (MAP) estimates of the magnitude of the clean speech DFT coefficients are derived. To exploit the temporal continuity of the speech and noise signals, a proper prior distribution is introduced by widening the posterior distribution of the NMF coefficients at the previous time frames. To do so, a recursive temporal update scheme is proposed to obtain the mean value of the prior distribution; also, the uncertainty of the prior information is governed by the shape parameter of the distribution which is learnt automatically based on the nonstationarity of the signals. Simulations show a considerable improvement compared to the maximum likelihood NMF based speech enhancement algorithm for different input SNRs.
Place, publisher, year, edition, pages
IEEE conference proceedings, 2012. 4561-4564 p.
, IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings, ISSN 1520-6149
Speech enhancement, NMF, MMSE, MAP
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:kth:diva-75458DOI: 10.1109/ICASSP.2012.6288933ISI: 000312381404158ScopusID: 2-s2.0-84867609546ISBN: 978-1-4673-0045-2OAI: oai:DiVA.org:kth-75458DiVA: diva2:490501
IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012; Kyoto; 25 March 2012 through 30 March 2012
FunderICT - The Next Generation
QC 201210152012-02-052012-02-052013-04-15Bibliographically approved