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Nobutaka Ono
Researcher at Tokyo Metropolitan University
Publications - 297
Citations - 5321
Nobutaka Ono is an academic researcher from Tokyo Metropolitan University. The author has contributed to research in topics: Blind signal separation & Non-negative matrix factorization. The author has an hindex of 34, co-authored 273 publications receiving 4572 citations. Previous affiliations of Nobutaka Ono include Metropolitan University & Hitotsubashi University.
Papers
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Proceedings ArticleDOI
Stable and fast update rules for independent vector analysis based on auxiliary function technique
TL;DR: Stable and fast update rules for independent vector analysis (IVA) based on auxiliary function technique that yield faster convergence and better results than natural gradient updates is presented.
Journal ArticleDOI
Determined blind source separation unifying independent vector analysis and nonnegative matrix factorization
TL;DR: This paper addresses the determined blind source separation problem and proposes a new effective method unifying independent vector analysis (IVA) and nonnegative matrix factorization (NMF) based on conventional multichannel NMF (MNMF), which reveals the relationship between MNMF and IVA.
Book ChapterDOI
The 2016 Signal Separation Evaluation Campaign
Antoine Liutkus,Fabian-Robert Stöter,Zafar Rafii,Daichi Kitamura,Bertrand Rivet,Nobutaka Ito,Nobutaka Ono,Julie Fontecave +7 more
TL;DR: The results of the 2016 community-based Signal Separation Evaluation Campaign (SiSEC 2016) are reported and the performance of the submitted systems are summarized.
Proceedings ArticleDOI
Complex NMF: A new sparse representation for acoustic signals
TL;DR: A new sparse representation for acoustic signals is presented which is based on a mixing model defined in the complex-spectrum domain (where additivity holds), and allows us to extract recurrent patterns of magnitude spectra that underlie observed complex spectra and the phase estimates of constituent signals.
Proceedings Article
Separation of a monaural audio signal into harmonic/percussive components by complementary diffusion on spectrogram
TL;DR: A simple and fast method to separate a monaural audio signal into harmonic and percussive components, which is much useful for multi-pitch analysis, automatic music transcription, drum detection, modification of music, and so on.