Reduced-rank modeling of time-varying spectral patterns for supervised source separation

Tomonori Fujiwara; Masao Yamagishi; Isao Yamada

ICASSP 2015accepted0 citations

Reduced-rank modeling of time-varying spectral patterns for supervised source separation

Tomonori Fujiwara, Masao Yamagishi, Isao Yamada

Abstract

In this paper, we propose a new modeling technique of signals having time-varying spectral patterns for supervised source separation. Typical examples of such signals are instrumental sounds having several segments such as “attack” and “sustain”. In the proposed technique, a given signal is modeled as a linear combination of multiple bases which are obtained by using reduced-rank representation of the given signal, where the number of bases is determined automatically. The proposed technique is used to generate the basis matrix in the context of supervised source separation, which improves conventional source separation methods.

BibTeX

@inproceedings{icassp2015_reducedrankmodel,
  title = {Reduced-rank modeling of time-varying spectral patterns for supervised source separation},
  author = {Tomonori Fujiwara and Masao Yamagishi and Isao Yamada},
  booktitle = {ICASSP 2015},
  year = {2015}
}