Proceedings ArticleDOI
Stable and fast update rules for independent vector analysis based on auxiliary function technique
Nobutaka Ono
- pp 189-192
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TLDR
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.Abstract:
This paper presents stable and fast update rules for independent vector analysis (IVA) based on auxiliary function technique. The algorithm consists of two alternative updates: 1) weighted covariance matrix updates and 2) demixing matrix updates, which include no tuning parameters such as step size. The monotonic decrease of the objective function at each update is guaranteed. The experimental evaluation shows that the derived update rules yield faster convergence and better results than natural gradient updates.read more
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A Consolidated Perspective on Multimicrophone Speech Enhancement and Source Separation
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Journal ArticleDOI
Determined blind source separation unifying independent vector analysis and nonnegative matrix factorization
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Book ChapterDOI
The 2018 Signal Separation Evaluation Campaign
TL;DR: SiSEC 2018 as mentioned in this paper was focused on audio and pursued the effort towards scaling up and making it easier to prototype audio separation software in an era of machine-learning-based systems.
Book ChapterDOI
The 2016 Signal Separation Evaluation Campaign
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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.
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A review of blind source separation methods: two converging routes to ILRMA originating from ICA and NMF
TL;DR: This paper describes several important methods for the blind source separation of audio signals in an integrated manner, and independent low-rank matrix analysis has been proposed, which integrates IVA and MNMF in a clever way.
References
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Proceedings Article
Algorithms for Non-negative Matrix Factorization
Daniel D. Lee,H. Sebastian Seung +1 more
TL;DR: Two different multiplicative algorithms for non-negative matrix factorization are analyzed and one algorithm can be shown to minimize the conventional least squares error while the other minimizes the generalized Kullback-Leibler divergence.
Journal ArticleDOI
Performance measurement in blind audio source separation
TL;DR: This paper considers four different sets of allowed distortions in blind audio source separation algorithms, from time-invariant gains to time-varying filters, and derives a global performance measure using an energy ratio, plus a separate performance measure for each error term.
Journal ArticleDOI
Blind separation of convolved mixtures in the frequency domain
TL;DR: It is observed that convolved Mixing in the time domain corresponds to instantaneous mixing in the frequency domain, and convolved mixing can be inverted using simpler and more robust algorithms than the ones recently developed.
Journal ArticleDOI
A robust and precise method for solving the permutation problem of frequency-domain blind source separation
TL;DR: By utilizing the harmonics of signals, the new method is robust even for low frequencies where DOA estimation is inaccurate, and provides an almost perfect solution to the permutation problem for a case where two sources were mixed in a room whose reverberation time was 300 ms.
Journal ArticleDOI
An approach to blind source separation based on temporal structure of speech signals
TL;DR: A new technique for blind source separation of speech signals by applying the decorrelation method proposed by Molgedey and Schuster in the time–frequency domain based on the temporal structure ofspeech signals is introduced.
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