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ICASSP
2009
IEEE
13 years 8 months ago
Multichannel nonnegative matrix factorization in convolutive mixtures. With application to blind audio source separation
We consider inference in a general data-driven object-based model of multichannel audio data, assumed generated as a possibly underdetermined convolutive mixture of source signals...
Alexey Ozerov, Cédric Févotte
TASLP
2010
157views more  TASLP 2010»
12 years 11 months ago
Multichannel Nonnegative Matrix Factorization in Convolutive Mixtures for Audio Source Separation
Abstract--We consider inference in a general data-driven object-based model of multichannel audio data, assumed generated as a possibly underdetermined convolutive mixture of sourc...
Alexey Ozerov, Cédric Févotte
ICASSP
2011
IEEE
12 years 8 months ago
Multichannel nonnegative tensor factorization with structured constraints for user-guided audio source separation
Separating multiple tracks from professionally produced music recordings (PPMRs) is still a challenging problem. We address this task with a user-guided approach in which the sepa...
Alexey Ozerov, Cédric Févotte, Rapha...
ICA
2010
Springer
13 years 5 months ago
Non-negative Hidden Markov Modeling of Audio with Application to Source Separation
Abstract. In recent years, there has been a great deal of work in modeling audio using non-negative matrix factorization and its probabilistic counterparts as they yield rich model...
Gautham J. Mysore, Paris Smaragdis, Bhiksha Raj
ICASSP
2010
IEEE
13 years 2 months ago
Blind rhythmic source separation: Nonnegativity and repeatability
An unsupervised method is proposed aiming at extracting rhythmic sources from commercial polyphonic music whose number of channels is limited to one. Commercial music signals are ...
Minje Kim, Jiho Yoo, Kyeongok Kang, Seungjin Choi