Generalized independent low-rank matrix analysis using heavy-tailed distributions for blind source separation

Generalized independent low-rank matrix analysis using heavy-tailed distributions for blind source separation

Abstract In this paper, statistical-model generalizations of independent low-rank matrix analysis (ILRMA) are proposed for achieving high-quality blind source separation (BSS). BSS is a crucial problem in realizing many audio applications, where the audio sources must be separated using only the obs...

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Bibliographic Details
Main Authors: Daichi Kitamura, Shinichi Mogami, Yoshiki Mitsui, Norihiro Takamune, Hiroshi Saruwatari, Nobutaka Ono, Yu Takahashi, Kazunobu Kondo
Format: Article
Language:English
Published: SpringerOpen 2018-05-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Blind audio source separation
Independent low-rank matrix analysis
Nonnegative matrix factorization
Student’s t distribution
Generalized Gaussian distribution
Online Access:http://link.springer.com/article/10.1186/s13634-018-0549-5

Internet

http://link.springer.com/article/10.1186/s13634-018-0549-5

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