Beyond the Narrowband Approximation: Wideband Convex Methods for Under-Determined Reverberant Audio Source Separation

作者：Kowalski Matthieu^*; Vincent Emmanuel; Gribonval Remi

来源：IEEE Transactions on Audio Speech and Language Processing, 2010, 18(7): 1818-1829.

DOI：10.1109/TASL.2010.2050089

• Convex optimization
• convolutive mixture
• mixed norms
• narrowband approximation
• source separation

We consider the problem of extracting the source signals from an under-determined convolutive mixture assuming known mixing filters. State-of-the-art methods operate in the time-frequency domain and rely on narrowband approximation of the convolutive mixing process by complex-valued multiplication in each frequency bin. The source signals are then estimated by minimizing either a mixture fitting cost or a source sparsity cost, under possible constraints on the number of active sources. In this paper, we define a wideband l(2) mixture fitting cost circumventing the above approximation and investigate the use of a l(1, 2) mixed-norm cost promoting disjointness of the source time-frequency representations. We design a family of convex functionals combining these costs and derive suitable optimization algorithms. Experiments indicate that the proposed wideband methods result in a signal-to-distortion ratio improvement of 2 to 5 dB compared to the state-of-the-art on reverberant speech mixtures.

• 出版日期2010-9
• 单位INRIA