Abstract: A method expands a bandwidth of an audio signal by determining a magnitude time-frequency representation |G(?, t) for example audio signals g(t). A set of frequency marginal probabilities PG(?|z) 221 are estimated from |G(?, t)|, and a magnitude time-frequency representation |X(?, t)| is determined from an input signal audio signal x(t). Probabilities P(z), PX(z) and PX(t|z) are determined using PG(?|z)|X(?, t)|. |?(?, t)| is reconstructed according to PzPX(z)PG(?|z)PX(t|z), and |?(?, t)| is transformed to a time domain to obtain a high-quality output audio signal ?(t) corresponding to the input audio signal x(t).

Abstract: Embodiments of the invention disclose a system and a method for reducing a dimensionality of a spectrogram matrix. The method constructs an intermediate time basis matrix and an intermediate frequency basis matrix and applies iteratively a non-negative matrix factorization (NMF) to the intermediate time basis matrix and the intermediate frequency basis matrix until a termination condition is reached, wherein the NMF is subject to a constraint on a an independence regularization term, wherein the constraint is in a form of a gradient of the term.

Abstract: A method expands a bandwidth of an audio signal by determining a magnitude time-frequency representation |G(?,t) for example audio signals g(t). A set of frequency marginal probabilities PG(?|z) 221 are estimated from |G(?,t)|, and a magnitude time-frequency representation |X(?,t)| is determined from an input signal audio signal x(t). Probabilities P(z), PX(z) and PX(t|z) are determined using PG(?|z)|X(?,t)|. |?(?,t)| is reconstructed according to PzPX(z)PG(?|z)PX(t|z), and ?(?,t)| is transformed to a time domain to obtain a high-quality output audio signal ?(t) corresponding to the input audio signal x(t).