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Computational Intelligence and Neuroscience
Volume 2008, Article ID 872425, 15 pages
http://dx.doi.org/10.1155/2008/872425
Research Article

Extended Nonnegative Tensor Factorisation Models for Musical Sound Source Separation

1Department of Electronic Engineering, Cork Institute of Technology, Cork, Ireland
2School of Electrical Engineering Systems, Dublin Institute of Technology, Kevin Street, Dublin, Ireland

Received 18 December 2007; Revised 3 March 2008; Accepted 17 April 2008

Academic Editor: Morten Morup

Copyright © 2008 Derry FitzGerald et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [54 citations]

The following is the list of published articles that have cited the current article.

  • Anh-Huy Phan, Petr Tichavsky, and Andrzej Cichocki, “Low rank tensor deconvolution,” 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2169–2173, . View at Publisher · View at Google Scholar
  • Yuki Mitsufuji, Shoichi Koyama, and Hiroshi Saruwatari, “Multichannel blind source separation based on non-negative tensor factorization in wavenumber domain,” 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 56–60, . View at Publisher · View at Google Scholar
  • Fabian-Robert Stoter, Antoine Liutkus, Roland Badeau, Bernd Edler, and Paul Magron, “Common fate model for unison source separation,” 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 126–130, . View at Publisher · View at Google Scholar
  • Delia Fano Yela, Sebastian Ewert, Derry FitzGerald, and Mark Sandler, “Interference reduction in music recordings combining Kernel Additive Modelling and Non-Negative Matrix Factorization,” 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 51–55, . View at Publisher · View at Google Scholar
  • Manh-Quan Bui, Viet-Hang Duong, Shih-Pang Tseng, Zhao-Ze Hong, Bo-Chang Chen, Zhi-Wei Zhong, and Jia-Ching Wang, “NMF/NTF-based methods applied for user-guided audio source separation: An overview,” 2016 International Conference on Orange Technologies (ICOT), pp. 80–83, . View at Publisher · View at Google Scholar
  • Umut Simsekli, Yusuf Cem Subakan, and Ali Taylan Cemgil, “A latent tensor factorization framework for non-negative convolutive models,” 2011 IEEE 19th Signal Processing and Communications Applications Conference (SIU), pp. 762–765, . View at Publisher · View at Google Scholar
  • Antoine Liutkus, Derry Fitzgerald, and Roland Badeau, “Cauchy nonnegative matrix factorization,” 2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), pp. 1–5, . View at Publisher · View at Google Scholar
  • Andrzej Cichocki, Rafal Zdunek, Anh Huy Phan, and Shun-Ichi Amaripp. 1–477, 2009. View at Publisher · View at Google Scholar
  • E. Vincent, N. Bertin, and R. Badeau, “Adaptive Harmonic Spectral Decomposition for Multiple Pitch Estimation,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 18, no. 3, pp. 528–537, 2010. View at Publisher · View at Google Scholar
  • Emmanuel Vincent, Maria G. Jafari, Samer A. Abdallah, Mark D. Plumbley, and Mike E. Daviespp. 162–185, 2010. View at Publisher · View at Google Scholar
  • Anssi Klapuri, Tuomas Virtanen, and Toni Heittola, “Sound source separation in monaural music signals using excitation-filter model and EM algorithm,” ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, pp. 5510–5513, 2010. View at Publisher · View at Google Scholar
  • Emmanuel Vincent, “Audio source separation using hierarchical phase-invariant models,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5933, pp. 12–16, 2010. View at Publisher · View at Google Scholar
  • Alexey Ozerov, Emmanuel Vincent, and Frédéric Bimbot, “A general modular framework for audio source separation,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6365, pp. 33–40, 2010. View at Publisher · View at Google Scholar
  • Pavel Krömer, Jan Platoš, and Václav Snášel, “Fast dimension reduction based on NMF,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6382, pp. 424–433, 2010. View at Publisher · View at Google Scholar
  • Pavel Krömer, Jan Platoš, and Václav Snašel, “Data mining using NMF and generalized matrix inverse,” Proceedings of the 2010 10th International Conference on Intelligent Systems Design and Applications, ISDA'10, pp. 409–414, 2010. View at Publisher · View at Google Scholar
  • M.D. Plumbley, A. Cichocki, and R. Bro, “Non-negative mixtures,” Handbook of Blind Source Separation, pp. 515–547, 2010. View at Publisher · View at Google Scholar
  • Li, Zhang, Liang, Zhang, and Fan, “Feature extraction for engine fault diagnosis utilizing the generalized S-transform and non-negative tensor factorization,” Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, vol. 225, no. 8, pp. 1936–1949, 2011. View at Publisher · View at Google Scholar
  • J. J. Carabias-Orti, T. Virtanen, P. Vera-Candeas, N. Ruiz-Reyes, and F. J. Canadas-Quesada, “Musical Instrument Sound Multi-Excitation Model for Non-Negative Spectrogram Factorization,” Ieee Journal Of Selected Topics In Signal Processing, vol. 5, no. 6, pp. 1144–1158, 2011. View at Publisher · View at Google Scholar
  • Umut Şimşekli, Yusuf Cem Sübakan, and Ali Taylan Cemgil, “A latent tensor factorization framework for non-negative convolutive models,” 2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011, pp. 762–765, 2011. View at Publisher · View at Google Scholar
  • Ali Taylan Cemgil, Umut Şimşekli, and Yusuf Cem Sübakan, “Probabilistic latent tensor factorization framework for audio modeling,” IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, pp. 137–140, 2011. View at Publisher · View at Google Scholar
  • Derry Fitzgerald, “Upmixing from mono - A source separation approach,” 17th DSP 2011 International Conference on Digital Signal Processing, Proceedings, 2011. View at Publisher · View at Google Scholar
  • Anssi Klapuri, “Pattern induction and matching in music signals,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6684, pp. 188–204, 2011. View at Publisher · View at Google Scholar
  • Christian Dittmar, Holger Großmann, Estefanía Cano, Sascha Grollmisch, Hanna Lukashevich, and Jakob Abeßer, “Songs2See and GlobalMusic2One: Two applied research projects in music information retrieval at Fraunhofer IDMT,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6684, pp. 259–272, 2011. View at Publisher · View at Google Scholar
  • Wenwu Wang, and Hafiz Mustafa, “Single channel music sound separation based on spectrogram decomposition and note classification,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6684, pp. 84–101, 2011. View at Publisher · View at Google Scholar
  • Cédric Févotte, and Alexey Ozerov, “Notes on nonnegative tensor factorization of the spectrogram for audio source separation: Statistical insights and towards self-clustering of the spatial cues,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6684, pp. 102–115, 2011. View at Publisher · View at Google Scholar
  • Rajesh Jaiswal, Derry FitzGerald, Dan Barry, Eugene Coyle, and Scott Rickard, “Clustering NMF basis functions using shifted NMF for monaural sound source separation,” ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, pp. 245–248, 2011. View at Publisher · View at Google Scholar
  • Alexey Ozerov, Emmanuel Vincent, and Frédéric Bimbot, “A general flexible framework for the handling of prior information in audio source separation,” IEEE Transactions on Audio, Speech and Language Processing, vol. 20, no. 4, pp. 1118–1133, 2012. View at Publisher · View at Google Scholar
  • Kazuyoshi Yoshii, and Masataka Goto, “A Nonparametric Bayesian Multipitch Analyzer Based on Infinite Latent Harmonic Allocation,” Ieee Transactions On Audio Speech And Language Processing, vol. 20, no. 3, pp. 717–730, 2012. View at Publisher · View at Google Scholar
  • Julian Mathias Becker, Martin Spiertz, and Volker Gnann, “A probability-based combination method for unsupervised clustering with application to blind source separation,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7191, pp. 99–106, 2012. View at Publisher · View at Google Scholar
  • Anh Huy Phan, Andrzej Cichocki, Petr Tichavský, and Zbyněk Koldovský, “On connection between the convolutive and ordinary nonnegative matrix factorizations,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7191, pp. 288–296, 2012. View at Publisher · View at Google Scholar
  • Julio J. Carabias-Orti, Maximo Cobos, Pedro Vera-Candeas, and Francisco J. Rodriguez-Serrano, “Nonnegative signal factorization with learnt instrument models for sound source separation in close-microphone recordings,” Eurasip Journal on Advances in Signal Processing, 2013. View at Publisher · View at Google Scholar
  • Yuki Mitsufuji, and Axel Roebel, “Sound source separation based on non-negative tensor factorization incorporating spatial cue as prior knowledge,” ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, pp. 71–75, 2013. View at Publisher · View at Google Scholar
  • Joachim Thiemann, and Emmanuel Vincent, “An experimental comparison of source separation and beamforming techniques for microphone array signal enhancement,” IEEE International Workshop on Machine Learning for Signal Processing, MLSP, 2013. View at Publisher · View at Google Scholar
  • Tom Barker, and Tuomas Virtanen, “Semi-supervised non-negative tensor factorisation of modulation spectrograms for monaural speech separation,” Proceedings of the International Joint Conference on Neural Networks, pp. 3556–3561, 2014. View at Publisher · View at Google Scholar
  • Emmanuel Vincent, Nancy Bertin, Remi Gribonval, and Frederic Bimbot, “From Blind to Guided Audio Source Separation [How models and side information can improve the separation of sound],” Ieee Signal Processing Magazine, vol. 31, no. 3, pp. 107–115, 2014. View at Publisher · View at Google Scholar
  • Yuki Mitsufuji, and Axel Roebel, “On the use of a spatial cue as prior information for stereo sound source separation based on spatially weighted non-negative tensor factorization,” Eurasip Journal on Advances in Signal Processing, 2014. View at Publisher · View at Google Scholar
  • Estefania Cano, Gerald Schuller, and Christian Dittmar, “Pitch-informed solo and accompaniment separation towards its use in music education applications,” Eurasip Journal on Advances in Signal Processing, 2014. View at Publisher · View at Google Scholar
  • Roland Badeau, and Mark D. Plumbley, “Multichannel High-Resolution NMF for Modeling Convolutive Mixtures of Non-Stationary Signals in the Time-Frequency Domain,” Ieee-Acm Transactions on Audio Speech and Language Processing, vol. 22, no. 11, pp. 1670–1680, 2014. View at Publisher · View at Google Scholar
  • Sebastian Ewert, Mark D. Plumbley, and Mark Sandler, “Accounting for phase cancellations in non-negative matrix factorization using weighted distances,” ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, pp. 649–653, 2014. View at Publisher · View at Google Scholar
  • Yuki Mitsufuji, Alex Baker, Marco Liuni, and Axel Roebel, “Online NON-negative Tensor Deconvolution for source detection in 3DTV audio,” ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, pp. 3082–3086, 2014. View at Publisher · View at Google Scholar
  • Umut Şimşekli, John R. Hershey, and Jonathan Le Roux, “Non-negative source-filter dynamical system for speech enhancement,” ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, pp. 6206–6210, 2014. View at Publisher · View at Google Scholar
  • Tianliang Peng, Yang Chen, and Zengli Liu, “A Time–Frequency Domain Blind Source Separation Method for Underdetermined Instantaneous Mixtures,” Circuits, Systems, and Signal Processing, 2015. View at Publisher · View at Google Scholar
  • Tuomas Virtanen, Jort F. Gemmeke, Bhiksha Raj, and Paris Smaragdis, “Compositional Models for Audio Processing,” Ieee Signal Processing Magazine, vol. 32, no. 2, pp. 125–144, 2015. View at Publisher · View at Google Scholar
  • Umut Şimşekli, Tuomas Virtanen, and Ali Taylan Cemgil, “Non-negative tensor factorization models for Bayesian audio processing,” Digital Signal Processing, 2015. View at Publisher · View at Google Scholar
  • Sayeh Mirzaei, Yaser Norouzi, and Hugo Van Hamme, “Two-stage blind audio source counting and separation of stereo instantaneous mixtures using Bayesian tensor factorisation,” Iet Signal Processing, vol. 9, no. 8, pp. 587–595, 2015. View at Publisher · View at Google Scholar
  • Derry FitzGerald, Antoine Liutkus, and Roland Badeau, “Projection-Based Demixing of Spatial Audio,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 24, no. 9, pp. 1556–1568, 2016. View at Publisher · View at Google Scholar
  • Tom Barker, and Tuomas Virtanen, “Blind Separation of Audio Mixtures Through Nonnegative Tensor Factorization of Modulation Spectrograms,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 24, no. 12, pp. 2377–2389, 2016. View at Publisher · View at Google Scholar
  • Sebastian Ewert, and Mark Sandler, “Piano Transcription in the Studio Using an Extensible Alternating Directions Framework,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 24, no. 11, pp. 1983–1997, 2016. View at Publisher · View at Google Scholar
  • Kamil Adiloglu, and Emmanuel Vincent, “Variational Bayesian Inference for Source Separation and Robust Feature Extraction,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 24, no. 10, pp. 1746–1758, 2016. View at Publisher · View at Google Scholar
  • Slim Essid, Sanjeel Parekh, Ngoc Q. K. Duong, Romain Serizel, Alexey Ozerov, Fabio Antonacci, and Augusto Sarti, “Multiview Approaches to Event Detection and Scene Analysis,” Computational Analysis of Sound Scenes and Events, pp. 243–276, 2017. View at Publisher · View at Google Scholar
  • Joonas Nikunen, and Tuomas Virtanen, “Source Separation and Reconstruction of Spatial Audio Using Spectrogram Factorization,” Parametric Time-Frequency Domain Spatial Audio, pp. 215–250, 2017. View at Publisher · View at Google Scholar
  • Masataka Goto, and Jordan B. L. Smith, “Nonnegative Tensor Factorization for Source Separation of Loops in Audio,” ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 2018-, pp. 171–175, 2018. View at Publisher · View at Google Scholar
  • Cédric Févotte, Emmanuel Vincent, and Alexey Ozerov, “Single-Channel Audio Source Separation with NMF: Divergences, Constraints and Algorithms,” Audio Source Separation, pp. 1–24, 2018. View at Publisher · View at Google Scholar
  • Alexey Ozerov, Cédric Févotte, and Emmanuel Vincent, “An Introduction to Multichannel NMF for Audio Source Separation,” Audio Source Separation, pp. 73–94, 2018. View at Publisher · View at Google Scholar