Abstract
Wiener filtering is one of the most widely used methods in audio source separation. It is often applied on time-frequency representations of signals, such as the short-time Fourier transform (STFT), to exploit their short-term stationarity, but so far the design of the Wiener time-frequency mask did not take into account the necessity for the output spectrograms to be consistent, i.e., to correspond to the STFT of a time-domain signal. In this paper, we generalize the concept of Wiener filtering to time-frequency masks which can involve manipulation of the phase as well by formulating the problem as a consistency-constrained Maximum-Likelihood one. We present two methods to solve the problem, one looking for the optimal time-domain signal, the other promoting consistency through a penalty function directly in the time-frequency domain. We show through experimental evaluation that, both in oracle conditions and combined with spectral subtraction, our method outperforms classical Wiener filtering.
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References
Diethorn, E.J.: Subband noise reduction methods for speech enhancement. In: Huang, Y., Benesty, J. (eds.) Audio Signal Processing for Next-Generation Multimedia Communication Systems, pp. 91–115. Kluwer, Dordrecht (2004)
Vincent, E., Jafari, M.G., Abdallah, S.A., Plumbley, M.D., Davies, M.E.: Probabilistic modeling paradigms for audio source separation. In: Machine Audition: Principles, Algorithms and Systems. IGI Global (to appear)
Le Roux, J., Ono, N., Sagayama, S.: Explicit consistency constraints for STFT spectrograms and their application to phase reconstruction. In: Proc. SAPA, pp. 23–28 (September 2008)
Le Roux, J., Kameoka, H., Vincent, E., Ono, N., Kashino, K., Sagayama, S.: Complex NMF under spectrogram consistency constraints. In: Proc. ASJ Autumn Meeting, (2-4-5) (September 2009)
Boll, S.: Suppression of acoustic noise in speech using spectral subtraction. IEEE Trans. ASSP 27, 113–120 (1979)
Griffin, D.W., Lim, J.S.: Signal estimation from modified short-time Fourier transform. IEEE Trans. ASSP 32(2), 236–243 (1984)
Lee, D.D., Seung, H.S.: Algorithms for non-negative matrix factorization. In: Proc. NIPS*2000, pp. 556–562. The MIT Press, Cambridge (2001)
Vincent, E., Gribonval, R., Plumbley, M.D.: BSS Oracle Toolbox Version 2.1, http://bass-db.gforge.inria.fr/bssoracle/
Vincent, E., Sawada, H., Bofill, P., Makino, S., Rosca, J.P.: First stereo audio source separation evaluation campaign: Data, algorithms and results. In: Proc. ICA, pp. 552–559 (September 2007)
Araki, S., Ozerov, A., Gowreesunker, V., Sawada, H., Theis, F., Nolte, G., Lutter, D., Duong, N.Q.: The 2010 signal separation evaluation campaign (SiSEC 2010) –Part II–: Audio source separation challenges. In: Proc. LVA/ICA (2010)
Yu, G., Mallat, S., Bacry, E.: Audio denoising by time-frequency block thresholding. IEEE Trans. Signal Process. 56(5), 1830–1839 (2008)
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Le Roux, J., Vincent, E., Mizuno, Y., Kameoka, H., Ono, N., Sagayama, S. (2010). Consistent Wiener Filtering: Generalized Time-Frequency Masking Respecting Spectrogram Consistency. In: Vigneron, V., Zarzoso, V., Moreau, E., Gribonval, R., Vincent, E. (eds) Latent Variable Analysis and Signal Separation. LVA/ICA 2010. Lecture Notes in Computer Science, vol 6365. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15995-4_12
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DOI: https://doi.org/10.1007/978-3-642-15995-4_12
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