Online algorithms for Nonnegative Matrix Factorization with the Itakura-Saito divergence

Details Online algorithms for Nonnegative Matrix Factorization with the Itakura-Saito divergence Online algorithms for Nonnegative Matrix Factorization with the Itakura-Saito divergence

2011-06-21

arxiv.org/abs/1106.4198v1

Statistics

Machine Learning

Scientific paper

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.

Affiliated with

Also associated with

No associations

Rating

Online algorithms for Nonnegative Matrix Factorization with the Itakura-Saito divergence does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Online algorithms for Nonnegative Matrix Factorization with the Itakura-Saito divergence, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Online algorithms for Nonnegative Matrix Factorization with the Itakura-Saito divergence will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-178615