Salem, Abderraouf BenSelouani, Sid AhmedHamam, Habib2020-01-302020-01-3020102010Salem, A. B., Selouani, S.-A., & Hamam, H. (2010). Auditory-based subband blind source separation using sample-by-sample and Infomax algorithms. In WCE 2010 - World Congress on Engineering 2010 (Vol. 1, pp. 651–655). http://www.iaeng.org/publication/WCE2010/WCE2010_pp651-655.pdf9789881701299http://www.iaeng.org/publication/WCE2010/WCE2010_pp651-655.pdfhttps://hdl.handle.net/20.500.12519/89We present a new subband decomposition method for the separation of convolutive mixtures of speech. This method uses a sample-by-sample algorithm to perform the subband decomposition by mimicking the processing performed by the human ear. The unknown source signals are separated by maximizing the entropy of a transformed set of signal mixtures through the use of a gradient ascent algorithm. Experimental results show the efficiency of the proposed approach in terms of signal-to-interference ratio. Compared with the fullband method that uses the Infomax algorithm, our method shows an important improvement of the output signal-to-noise ratio when the sensor inputs are severely degraded by additive noise.enConvolutive mixtureConvolutive sourcesEar modelFull bandGradient ascentHuman earInfomax algorithmInfomax algorithmsOutput signal-to-noise ratiosSensor inputsSignal to interference ratioSource signalsSub-bandsSubband decompositionSignal to noise ratioBlind source separationConference PaperCopyright : 2010 International Association of Engineers