Time-domain Blind Audio Source Separation Method Producing Separating Filters of Generalized Feedforward Structure

0348111 20240111140745.220101102235959.9 Time-domain Blind Audio Source Separation Method Producing Separating Filters of Generalized Feedforward Structure 8 s. www cav_un_epca*0348107978-3-642-15994-7Lecture Notes in Computer Science636517-24HeidelbergSpringer-Verlag2010GavrilovaM.L.KumarV.MunY.TanC.J.K.GervasiO. blind source separation audio convolutive mixture 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. cav_un_auth*0050739 Málek J. CZ http://library.utia.cas.cz/separaty/2010/SI/tichavsky-time-domain blind audio source separation method producing separating filters of generalized feedforward structure.pdf 324kB 1M0572 GA MŠk cav_un_auth*0001814 GA102/09/1278 GA ČR cav_un_auth*0253174 CEZ:AV0Z10750506 Time-domain methods for blind separation of audio signals are preferred due to their lower demand for available data and the avoidance of the permutation problem. However, their computational demands increase rapidly with the length of separating filters due to the simultaneous growth of the dimension of an observation space. We propose, in this paper, a general framework that allows the time-domain methods to compute separating filters of theoretically infinite length without increasing the dimension. Based on this framework, we derive a generalized version of the time-domain method of Koldovsky and Tichavsky (2008). For instance, it is demonstrated that its performance might be improved by 4dB of SIR using the Laguerre filter bank. 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/11104/0188723 2010 324kB cav_un_epca*0348107 Lecture Notes in Computer Science 6365 978-3-642-15994-7 17 24 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