Abstract
Blind source separation (BSS) and dereverberation have been deeply investigated due to their importance in many applications, as in image and audio processing. A two-stage approach leading to a sequential source separation and speech dereverberation algorithm based on blind channel identification (BCI) has recently appeared in literature and taken here as reference. In this contribution, a real-time implementation of the aforementioned approach is presented. The optimum inverse filtering algorithm based on the Bezout’s Theorem and used in the dereverberation stage has been substituted with an iterative technique, which is computationally more efficient and allows the inversion of long impulse responses in real-time applications. The entire framework works in frequency domain and the NU-Tech software platform has been used on purpose for real-time simulations.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Campbell, D.: Roomsim, a matlab simulation of shoebox room acoustics for use in teaching and research, http://media.paisley.ac.uk/~campbell/Roomsim/
Haque, M., Bashar, M., Naylor, P., Hirose, K., Hasan, M.: Energy constrained frequency-domain normalized lms algorithm for blind channel identification. Signal, Image and Video Processing (3), 203–213 (2007)
Haque, M., Hasan, M.: Variable step size frequency domain multichannel lms algorithm for blind channel identification with noise. In: Proc. Communication Systems, Networks and Digital Signal Processing (2006)
Hikichi, T., Delcroix, M., Miyoshi, M.: Inverse Filtering for Speech Dereverberation Less Sensitive to Noise and Room Transfer Function Fluctuations. EURASIP Journal on Advances in Signal Processing 2007, 1–13 (2007)
Huang, Y., Benesty, J., Chen, J.: A blind channel identification-based two-stage approach to separation and dereverberation of speech signals in a reverberant environment. IEEE Transactions on Speech and Audio Processing 13(5), 882–895 (2005)
Huang, Y., Benesty, J.: A class of frequency-domain adaptive approaches to blind multichannel identification. IEEE Transactions on Signal Processing 51(1), 11–24 (2003)
Rotili, R., Cifani, S., Principi, E., Squartini, S., Piazza, F.: A robust iterative inverse filtering approach for speech dereverberation in presence of disturbances. In: APCCAS 2008 - 2008 IEEE Asia Pacific Conference on Circuits and Systems, pp. 434–437 (2008)
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. In: Proceedings of 118th Convention of the Audio Engineering Society (2005)
Xu, G., Liu, H., Tong, L., Kailath, T.: A Least-Squares Approach to Blind Channel Identification. IEEE Transactions on Signal Processing 43(12), 2982–2993 (1995)
Yu, Z., Er, M.: A robust adaptive blind multichannel identification algorithm for acoustic applications. IEEE International Conference on Acoustics, Speech, and Signal Processing (2), ii–25–8 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rotili, R., De Simone, C., Perelli, A., Cifani, S., Squartini, S. (2010). Joint Multichannel Blind Speech Separation and Dereverberation: A Real-Time Algorithmic Implementation. In: Huang, DS., McGinnity, M., Heutte, L., Zhang, XP. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Communications in Computer and Information Science, vol 93. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14831-6_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-14831-6_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14830-9
Online ISBN: 978-3-642-14831-6
eBook Packages: Computer ScienceComputer Science (R0)