0348108 20240111140745.220101102235959.9 8 s. memory stick cav_un_epca*0348107978-3-642-15994-763659-16HeidelbergSpringer-Verlag2010GavrilovaM.L.KumarV.MunY.TanC.J.K.GervasiO. blind source separation speech convolutive mixture adaptive algorithms cav_un_auth*0050739 Málek J. CZ cav_un_auth*0108100 Koldovský Zbyněk Stochastická informatika Department of Stochastic Informatics SI SI UTIA-B Department of Stochastic Informatics Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101212 Tichavský Petr Stochastická informatika Department of Stochastic Informatics SI SI UTIA-B Department of Stochastic Informatics Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2010/SI/tichavsky-adaptive time-domain blind separation of speech signals.pdf 281kB 1M0572 GA MŠk cav_un_auth*0001814 GA102/09/1278 GA ČR cav_un_auth*0253174 GA102/08/0707 GA ČR CZ CEZ:AV0Z10750506 We present an adaptive algorithm for blind audio source separation (BASS) of moving sources via Independent Component Analysis (ICA) in time-domain. The method is shown to achieve good separation quality even with a short demixing filter length (L = 30). Our experiments show that the proposed adaptive algorithm can outperform the off-line version of the method (in terms of the average output SIR), even in the case in which the sources do not move, because it is capable of better adaptation to the nonstationarity of the speech. cav_un_auth*0264720 Latent Variable Analysis and Signal Separation St. Malo 27.09.2010-30.09.2010 FR 2011 BB http://hdl.handle.net/11104/0188720 2010 281kB cav_un_epca*0348107 Lecture Notes in Computer Science 6365 978-3-642-15994-7 9 16 Heidelberg Springer-Verlag 2010 Latent Variable Analysis and Signal Separation, 9th Int. Conf., LVA/ICA 2010 Gavrilova M.L. 340 Kumar V. 340 Mun Y. 340 Tan C.J.K. 340 Gervasi O. 340