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.
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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
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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
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