Nonnegative Matrix Factor 2-D Deconvolution for Blind Single Channel Source Separation
|Mikkel N. Schmidt, Morten Mørup|
|Abstract||We present a novel method for blind separation of instruments|
in polyphonic music based on a non-negative matrix factor 2-D
deconvolution algorithm. Using a model which is convolutive in both
time and frequency we factorize a spectrogram representation of music
into components corresponding to individual instruments. Based on
this factorization we separate the instruments using spectrogram masking.
The proposed algorithm has applications in computational auditory
scene analysis, music information retrieval, and automatic music transcription.
|Keywords||non-negative matrix factorization, blind source separation|
|Type||Conference paper [With referee]|
|Conference||International Conference on Independent Component Analysis and Signal Separation|
|Year||2006 Month April|
|BibTeX data|| [bibtex]|
|IMM Group(s)||Intelligent Signal Processing|