Title :
Non-negative matrix completion for bandwidth extension: A convex optimization approach
Author :
Sun, Dennis L. ; Mazumder, Rahul
Abstract :
Bandwidth extension is the problem of recovering missing bandwidth in audio signals that have been band-passed, typically for compression purposes. One approach that has been shown to be successful for bandwidth extension is non-negative matrix factorization (NMF). The disadvantage of NMF is that it is non-convex and intractable to solve in general. However, in bandwidth extension, only the reconstruction is needed and not the explicit factors. We formulate bandwidth extension as a convex optimization problem, propose a simple algorithm, and demonstrate the effectiveness of this approach on practical examples.
Keywords :
audio coding; data compression; matrix decomposition; NMF; audio compression; band-pass audio signals; bandwidth extension; convex optimization approach; nonnegative matrix completion; nonnegative matrix factorization; Bandwidth; Convex functions; Harmonic analysis; Spectrogram; Speech; Training; Training data; bandwidth extension; nonnegative matrix factorization; source separation;
Conference_Titel :
Machine Learning for Signal Processing (MLSP), 2013 IEEE International Workshop on
Conference_Location :
Southampton
DOI :
10.1109/MLSP.2013.6661924