Blind Audio Source Separation

We deal with the case where the sources are linearly mixed and the mixtures are underdetermined. Hence, A has more columns than rows. Sparsity of the sources is vital for good separation. Bayesian methods such as the Gibbs Sampler (a standard MCMC simulation method) are used to estimate the sources and the mixing matrix in the presence of noise.

I.I.D. Gaussian noise was added to the observations, which resulted in an SNR of about 16 dB. The mixing matrix used is given by A = [0.4000 0.8315 0.5657; -0.6928 -0.3444 0.5657].

1) Introduction
2) Speech Signals
3) Musical Signals
4) Percussion Signals
5) Combination of Signals
6) Overcomplete Dictionaries
7) Conclusion

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