Details

Title

ICA-based Single Channel Audio Separation: New Bases and Measures of Distance

Journal title

Archives of Acoustics

Yearbook

2011

Volume

vol. 36

Numer

No 2

Authors

Keywords

audio unmixing ; blind signal separation ; independent component analysis ; measures of distance

Divisions of PAS

Nauki Techniczne

Coverage

311-331

Publisher

Committee on Acoustics PAS, PAS Institute of Fundamental Technological Research, Polish Acoustical Society

Date

2011

Type

Artykuły / Articles

Identifier

ISSN 0137-5075 ; eISSN 2300-262X

References

Bach F. (2005), Blind one-microphone speech separation: A spectral learning approach, Advances in neural information processing systems, 17, 65. ; Barry D. (2005), Single Channel Source Separation using Short-time Independent Component Analysis, null. ; Barry D. (2004), Sound source separation: azimuth discrimination and resynthesise, null. ; Bech S. (2006), Perceptual Audio Evaluation, doi.org/10.1002/9780470869253 ; Box G. (1973), Bayesian Inference In Statistical Analysis. ; Brungart D. (2006), Isolating the energetic component of speech-on-speech masking with ideal t-f segregation, Journal Acoustical Society of America, 120, 4007, doi.org/10.1121/1.2363929 ; Cardoso J.-F. (1998), Blind Signal Separation: statistical principles, Proceedings of the IEEE, 9, 10, 2009, doi.org/10.1109/5.720250 ; Casey M. (2001), Separation of Mixed Audio Sources by Independent Subspace Analysis. ; Cooney R. (2006), An Enhanced implementation of the ADRess (Azimuth Discrimination and Resynthesis) Music Source Separation Algorithm. ; Cover T. (1991), Elements of Information Theory, doi.org/10.1002/0471200611 ; Davies M. (2007), Source separation using single channel ICA, Signal Process, 87, 8, 1819, doi.org/10.1016/j.sigpro.2007.01.011 ; Duan Z. (2008), Unsupervised Single-Channel Music Source Separation by Average Harmonic Structure Modeling, IEEE Transactions on Audio, Speech and Language Processing, 16, 4, 766, doi.org/10.1109/TASL.2008.919073 ; Dziubinski M. (2010), Evaluation of the separation algorithm performance employing ANNs, 27. ; Hyvarinen A. (2001), Independent Component Analysis, doi.org/10.1002/0471221317 ; Jain A. (1988), Algorithms for Clustering Data. ; Jain A. (1999), Data Clustering: A Review, ACM Computing Survey, 31, 3. ; Jang G.-J. (2002), Learning statistically efficient features for speaker recognition, Neurocomputing, 49, 1. ; Jang G.-J. (2003), A Maximum Likelihood Approach to Single-Channel Source Separation, Journal of Machine Learning Research, 4, 1365. ; Kostek B. (2005), Perception-Based Data Processing in Acoustics. ; Lee T.-W., Lewicki M.S. (2000), <i>The generalized Gaussian Mixture Model using ICA, International workshop on ICA</i>, 239-244. ; Litvin, Y., Cohen I. (2009), <i>Single-channel source separation of audio signals using Bark Scale Wavelet Packet Decomposition</i>, IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2009, 1-4. ; Masters A.S. (2006), <i>Stereo music source separation via Bayesian modeling</i>, Ph.D. dissertation, Stanford University, USA. ; McQueen J. (1967), Some methods for classification and analysis of multivariate observations, null, 281. ; Mijovic' B. (2010), Source Separation From Single-Channel Recordings by Combining Empirical-Mode Decomposition and Independent Component Analysis, IEEE Transactions on Biomedical Engineering, 57, 9, 2188, doi.org/10.1109/TBME.2010.2051440 ; Mika D. (2009), <i>Separation of sounds from various sources in a mixed acoustic signal</i> [in Polish], Ph.D. Thesis, AGH University, Kraków, Poland. ; Paatero P. (1997), Least squares formulation of robust non-negative factor analysis, Chemometr. Intell. Lab, 37, 1, 23, doi.org/10.1016/S0169-7439(96)00044-5 ; Papoulis A. (1991), Probability, Random Variables, and Stochastic Processes. ; Rickard S. (2002), On the approximate W-disjoint orthogonality of speech, 529. ; Seber G. (1984), Multivariate Observations, doi.org/10.1002/9780470316641 ; Taghia J. (2009), Subband-based Single-channel Source Separation of Instantaneous Audio Mixtures World, World Applied Sciences Journal, 6, 784. ; Vinyes M. (2006), Demixing Commercial Music Productions via Human-Assisted T-f Masking. ; Wang D. (2006), Computational auditory scene analysis, Principles, Algorithms, and Applications. ; Wang B. (2006), Investigating single-channel audio source separation methods based on non-negative matrix factorization. ; Yilmaz O. (2004), Blind separation of speech mixtures via t-f masking, IEEE Transactions on Signal Processing, 52, 7, 1830, doi.org/10.1109/TSP.2004.828896

DOI

10.2478/v10168-011-0024-x

×