Latent Variable Analysis and Signal Separation

1. Front Matter

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2. Speech and Audio Applications

   1. Blind Source Separation Based on Time-Frequency Sparseness in the Presence of Spatial Aliasing

      • Benedikt Loesch, Bin Yang

      Pages 1-8

   2. Adaptive Time-Domain Blind Separation of Speech Signals

      • Jiří Málek, Zbyněk Koldovský, Petr Tichavský

      Pages 9-16

   3. Time-Domain Blind Audio Source Separation Method Producing Separating Filters of Generalized Feedforward Structure

      • Zbyněk Koldovský, Petr Tichavský, Jiří Málek

      Pages 17-24

   4. Subband Blind Audio Source Separation Using a Time-Domain Algorithm and Tree-Structured QMF Filter Bank

      • Zbyněk Koldovský, Petr Tichavský, Jiří Málek

      Pages 25-32

   5. A General Modular Framework for Audio Source Separation

      • Alexey Ozerov, Emmanuel Vincent, Frédéric Bimbot

      Pages 33-40

   6. Adaptive Segmentation and Separation of Determined Convolutive Mixtures under Dynamic Conditions

      • Benedikt Loesch, Bin Yang

      Pages 41-48

   7. Blind Speech Extraction Combining Generalized MMSE STSA Estimator and ICA-Based Noise and Speech Probability Density Function Estimations

      • Hiroshi Saruwatari, Ryoi Okamoto, Yu Takahashi, Kiyohiro Shikano

      Pages 49-56

   8. Blind Estimation of Locations and Time Offsets for Distributed Recording Devices

      • Keisuke Hasegawa, Nobutaka Ono, Shigeki Miyabe, Shigeki Sagayama

      Pages 57-64

   9. Speech Separation via Parallel Factor Analysis of Cross-Frequency Covariance Tensor

      • Xiao-Feng Gong, Qiu-Hua Lin

      Pages 65-72

   10. Under-Determined Reverberant Audio Source Separation Using Local Observed Covariance and Auditory-Motivated Time-Frequency Representation

       • Ngoc Q. K. Duong, Emmanuel Vincent, Rémi Gribonval

       Pages 73-80

   11. Crystal-MUSIC: Accurate Localization of Multiple Sources in Diffuse Noise Environments Using Crystal-Shaped Microphone Arrays

       • Nobutaka Ito, Emmanuel Vincent, Nobutaka Ono, Rémi Gribonval, Shigeki Sagayama

       Pages 81-88

3. Convolutive Signal Separation

   1. Consistent Wiener Filtering: Generalized Time-Frequency Masking Respecting Spectrogram Consistency

      • Jonathan Le Roux, Emmanuel Vincent, Yuu Mizuno, Hirokazu Kameoka, Nobutaka Ono, Shigeki Sagayama

      Pages 89-96

   2. Blind Separation of Convolutive Mixtures of Non-stationary Sources Using Joint Block Diagonalization in the Frequency Domain

      • Hicham Saylani, Shahram Hosseini, Yannick Deville

      Pages 97-105

   3. Single Microphone Blind Audio Source Separation Using EM-Kalman Filter and Short+Long Term AR Modeling

      • Siouar Bensaid, Antony Schutz, Dirk T. M. Slock

      Pages 106-113

4. The 2010 Signal Separation Evaluation Campaign (SiSEC2010)

   1. The 2010 Signal Separation Evaluation Campaign (SiSEC2010): Audio Source Separation

      • Shoko Araki, Alexey Ozerov, Vikrham Gowreesunker, Hiroshi Sawada, Fabian Theis, Guido Nolte et al.

      Pages 114-122

   2. The 2010 Signal Separation Evaluation Campaign (SiSEC2010): Biomedical Source Separation

      • Shoko Araki, Fabian Theis, Guido Nolte, Dominik Lutter, Alexey Ozerov, Vikrham Gowreesunker et al.

      Pages 123-130

5. Audio

   1. Use of Bimodal Coherence to Resolve Spectral Indeterminacy in Convolutive BSS

      • Qingju Liu, Wenwu Wang, Philip Jackson

      Pages 131-139

   2. Non-negative Hidden Markov Modeling of Audio with Application to Source Separation

      • Gautham J. Mysore, Paris Smaragdis, Bhiksha Raj

      Pages 140-148

   3. Nonnegative Matrix Factorization with Markov-Chained Bases for Modeling Time-Varying Patterns in Music Spectrograms

      • Masahiro Nakano, Jonathan Le Roux, Hirokazu Kameoka, Yu Kitano, Nobutaka Ono, Shigeki Sagayama

      Pages 149-156

This book constitutes the proceedings of the 9th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2010, held in St. Malo, France, in September 2010.


The 25 papers presented were carefully reviewed and selected from over hundred submissions. The papers collected in this volume demonstrate that the research activity in the field continues to gather theoreticians and practitioners, with contributions ranging range from abstract concepts to the most concrete and applicable questions and considerations. Speech and audio, as well as
biomedical applications, continue to carry the mass of the considered applications. Unsurprisingly the concepts of sparsity and non-negativity, as well as tensor decompositions, have become predominant, reflecting the strongactivity on these themes in signal and image processing at large.

• EEG
• MIMO
• Online
• Segment
• blind source separation
• interference cancellation
• matrix factorization
• noice cancellation
• phase analysis
• semantic indexing
• signal processing
• signal separation
• sparse component analysis
• subspace analysis
• vector analysis
• algorithm analysis and problem complexity

• Dept. of Electrical Engineering, Universitè d’Evry Val d’Essone, Courcouronnes, France

  Vincent Vigneron

• Laboratoire I3S, Les Algorithmes - Euclide-B, BP 121, Université de Nice-Sophia Antipolis, Sophia Antipolis Cedex, France

  Vicente Zarzoso

• School of Engineering, Dept. of Telecommunications, ISITSchool of Engineering, Dept. of Telecommunications, ISITV, Université de Toulon, 83162, France

  Eric Moreau

• INRIA France, Equipe-projet METISS, Centre de Recherche INRIA Rennes-Bretagne Atlantique, Rennes cedex, France

  Rémi Gribonval

• INRIA France, Equipe-projet METISS, Centre de Recherche INRIA Rennes-Bretagne Atlantique, Rennes Cedex, France

  Emmanuel Vincent

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