Abstract
Several efforts have been put by the international scientific community on the Speech Enhancement (SE) research field, specially for the several applications it may have (like human-machine dialogue systems and speaker identification/verification). An innovative SE scheme is presented in this work: it integrates the spatial method (Blind Source Separation, BSS) with the temporal method (Adaptive Noise Canceller, ANC) and a final stage composed of a Multichannel Signal Detection and a Post Filter (MSD+PF) to enhance vocal signals in noisy and reverberant environment. We used a broadband blind source separation (BSS) algorithm to separate target and interference signals in real reverberant scenarios and the two post-processing stages ANC and MSD+PF, in cascade with the first one, to improve the separation yielded by the BSS. In particular the former one allows to further reduce the residual interference signal still presents in the desired target signal after separation, by using as reference the other output of the BSS stage. Computer real-time simulations show progressive improvements across the different processing stages in terms of the chosen quality parameter, i.e. the coherence between the two output channels.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Van Veen, B.D., Buckley, K.M.: Beamforming: A versatile approach to spatial filtering. IEEE Acoust., Speech and Signal Process. Magazine 5, 4–24 (1988)
Kellermann, W.: A self-steering digital microphone array. In: IEEE Int. Conf. on Acust., and Signal Process, vol. 5, pp. 3581–3584 (1991)
Smaragdis, P.: Efficient blind separation of convolved sound mixtures. IEEE Apps. Signal Process. Audio Acoust., 19–22 (1997)
Low, S.Y., Nordholm, S., Togneri, S.: Convolutive Blind Signal Separation with Post-Processing. IEEE Trans. on Speech and Audio Proc. 12, 539–548 (2004)
Aichner, R., Buchner, H., Yan, F., Kellermann, W.: A real-time blind source separation scheme and its application to reverberant and noisy acoustic environments. In: Aichner, R., Buchner, H., Yan, F., Kellermann, W. (eds.) IEEE Int. Conf. on Acust., and Signal Process, Multimedia Communications and Signal Processing, University of Erlangen-Nuremberg (Available online October 21, 2005)
Cifani, S., Principi, E., Rocchi, C., Squartini, S., Piazza, F.: A Multichannel Noise Reduction Front-End based on Psychoacoustics for robust speech recognition in highly noisy environment. In: Proc. of HSCMA 2008, Trento, Italy, May 6-8, pp. 172–176 (2008)
Greenberg, J.E.: Modified LMS Algorithms for Speech Processing with an Adaptive Noise Canceller. IEEE Trans. on Speech and Audio Process. 6(4), 338–350 (1998)
Gannot, S., Cohen, I.: Speech enhancement based on the general transfer function GSC and postfiltering. IEEE Trans. on Speech and Audio Proc. 12(6) (2004)
Cichocki, A., Amari, S.: Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications. John Wiley & Sons, Inc., Chichester (2002)
Fancourt, C.L., Parra, L.: The coherence function in blind source separation of convolutive mixtures of non-stationary signals. In: Proc. NNSP, pp. 303–312 (2001)
Buchner, H., Aichner, R., Kellermann, W.: A generalization of blind source separation algorithms for convolutive mixtures based on secondorder statistics. IEEE Trans. Speech Audio Process. 13(1), 120–134 (2005)
Buchner, H., Aichner, R., Kellermann, W.: A generalization of a class of blind source separation algorithms for convolutive mixtures. In: Proceedings of the International Symposium of Independent Component Analysis and Blind Signal Separation (ICA), Nara, Japan, April 2003, pp. 945–950 (2003)
Cohen, I.: Noise spectrum estimation in adverse environments: improved minima controlled recursive averaging. IEEE Trans. on Speech and Audio Proc. 11(5) (2003)
Squartini, S., Ciavattini, E., Lattanzi, A., Zallocco, D., Bettarelli, F., Piazza, F.: NU-Tech: implementing DSP Algorithms in a plug-in based software platform for Real Time Audio applications. Presented at the 118th AES Convention, Barcelona, Spain, May 28-31 (2005)
Hansen, J.H.L., Pellom, B.L.: An effective quality evaluation protocol for speech enhancement algorithms. In: ICSLP 1998, paper 0917, Sydney, Australia, November 30 - December 4 (1998)
Carter, G.C., Knapp, C.H., Nuttall, A.H.: Estimation of the magnitude squared coherence function via overlapped fast Fourier transform processing. IEEE Trans. on Audio and Electroacoustics 21(4), 337–344 (1973)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pignotti, A., Marcozzi, D., Cifani, S., Squartini, S., Piazza, F. (2009). A Blind Source Separation Based Approach for Speech Enhancement in Noisy and Reverberant Environment. In: Esposito, A., Vích, R. (eds) Cross-Modal Analysis of Speech, Gestures, Gaze and Facial Expressions. Lecture Notes in Computer Science(), vol 5641. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03320-9_33
Download citation
DOI: https://doi.org/10.1007/978-3-642-03320-9_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03319-3
Online ISBN: 978-3-642-03320-9
eBook Packages: Computer ScienceComputer Science (R0)