Online algorithms for nonnegative matrix factorization with the Itakura-Saito divergence
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- 1 October 2011
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- No. 19311168,p. 313-316
Abstract
Nonnegative matrix factorization (NMF) is now a common tool for audio source separation. When learning NMF on large audio databases, one major drawback is that the complexity in time is O(FKN) when updating the dictionary (where (F, N) is the dimension of the input power spectrograms, and K the number of basis spectra), thus forbidding its application on signals longer than an hour. We provide an online algorithm with a complexity of O(FK) in time and memory for updates in the dictionary. We show on audio simulations that the online approach is faster for short audio signals and allows to analyze audio signals of several hours.Keywords
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This publication has 3 references indexed in Scilit:
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- Nonnegative Matrix Factorization with the Itakura-Saito Divergence: With Application to Music AnalysisNeural Computation, 2009
- Supervised and Semi-supervised Separation of Sounds from Single-Channel Mixtures2007