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RESEARCH [B - C]
Scroll down to find direct links to publicly posted research papers, presentations, etc. in the field of sound source separation and related topics. I have listed them in alphabetical order by title for ease of browsing and have provided these links, which are available on the web, for your convenience. I have provided permalinks for those papers available for a fee. Titles without a link can be found through a web search. Please use the CONTACT page to notify me of any corrections, to supply suggestions for adding any additional pertinent links, or to notify me if you encounter any dead links in this list. Thanks!
BACH10 SCORE-INFORMED SEPARATION ISMIR2017
Marius Miron, Music Technology Group, Universitat Pompeu Fabra, Barcelona (2017)
BANDWIDTH EXTENSION OF MUSICAL AUDIO SIGNALS WITH NO SIDE INFORMATION USING DILATED CONVOLUTIONAL NEURAL NETWORKS [PDF]
Mathieu Lagrange, Félix Gontier, LS2N, CNRS, Centrale Nantes, France (2020)
BAYESIAN ANISOTROPIC GAUSSIAN MODEL FOR AUDIO SOURCE SEPARATION [PDF]
Paul Magron, Tuomas Virtanen, Laboratory of Signal Processing, Tampere University of Technology, Finland (2017)
BAYESIAN ANISOTROPIC GAUSSIAN MODEL FOR AUDIO SOURCE SEPARATION (slides) [PDF]
Paul Magron, Tuomas Virtanen, Laboratory of Signal Processing, Tampere University of Technology, Finland (2018)
BAYESIAN EXTENSIONS TO NON-NEGATIVE MATRIX FACTORISATION FOR AUDIO SIGNAL MODELLING [PDF]
Tuomas Virtanen, A. Taylan Cemgil, Simon Godsill, Signal Processing and Communications Laboratory, University of Cambridge, Department of Engineering, Cambridge, UK (2008)
BAYESIAN FACTORIZATION AND LEARNING FOR MONAURAL SOURCE SEPARATION [permalink]
Jen-Tzung Chien, Po-Kai Yang, Dept. of Electr. & Comput. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan (2016)
BAYESIAN FACTORIZATION AND SELECTION FOR SPEECH AND MUSIC SEPARATION [PDF]
Po-Kai Yang, Chung-Chien Hsu and Jen-Tzung Chien, Department of Electrical and Computer Engineering, National Chiao Tung University, Taiwan (2014)
BAYESIAN GROUP SPARSE LEARNING FOR MUSIC SOURCE SEPARATION [PDF]
Jen-Tzung Chien and Hsin-Lung Hsieh, Department of Electrical and Computer Engineering, National Chiao Tung University, Taiwan, Republic of China (2013)
BAYESIAN HIERARCHICAL MODELING FOR MUSIC AND AUDIO PROCESSING AT LABROSA (slides) [PDF]
Dawen Liang (LabROSA), Joint work with: Dan Ellis (LabROSA), Matt Hoffman (Adobe Research), Gautham Mysore (Adobe Research) (2014)
BAYESIAN NMF WITH GROUP SPARSITY AND ITS APPLICATION FOR MUSIC SOURCE SEPARATION (in Chinese) [permalink]
Tsung-Han Lin, Institute of Computer Science and Information Engineering, Taiwan, R.O.C
BAYESIAN NONNEGATIVE MATRIX FACTORIZATION FOR MONAURAL AUDIO SOURCE SEPARATION
Po-Kai Yang, Machine Learning Laboratory, Department of Electrical and Computer Engineering, National Chiao Tung University, Taiwan (2014)
BAYESIAN NON-NEGATIVE MATRIX FACTORIZATION WITH LEARNED TEMPORAL SMOOTHNESS PRIORS [permalink]
Mathieu Coïc and Juan José Burred, Audionamix, Paris, France (2012)
BAYESIAN NONPARAMETRIC MATRIX FACTORIZATION FOR RECORDED MUSIC [PDF]
Matthew D. Hoffman, David M. Blei, Perry R. Cook, Princeton University, Department of Computer Science, Princeton, New Jersey, USA (2010)
BAYESIAN NONPARAMETRIC SPECTROGRAM MODELING BASED ON INFINITE FACTORIAL INFINITE HIDDEN MARKOV MODEL [permalink]
Masahiro Nakano†, Jonathan Le Roux‡, Hirokazu Kameoka‡, Tomohiko Nakamura†, Nobutaka Ono† and Shigeki Sagayama†, †Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan, ‡NTT Communication Science Laboratories, NTT Corporation, Kanagawa, Japan (2011)
BAYESIAN SINGING-VOICE SEPARATION [PDF]
Po-Kai Yang, Chung-Chien Hsu and Jen-Tzung Chien, Department of Electrical and Computer Engineering, National Chiao Tung University, Taiwan (2014)
BAYESIAN SOURCE SEPARATION (slides) [PDF]
Jen-Tzung Chien, Department of Electrical and Computer Engineering, National Chiao Tung University, Taiwan (2015)
BAYESIAN STATISTICAL METHODS FOR AUDIO AND MUSIC PROCESSING [PDF]
A. Taylan Cemgil, Simon J. Godsill, Paul Peeling, Nick Whiteley, Signal Processing and Comms. Lab, University of Cambridge, Department of Engineering, Cambridge, UK (2008)
BENCHMARKING FLEXIBLE ADAPTIVE TIME-FREQUENCY TRANSFORMS FOR UNDERDETERMINED AUDIO SOURCE SEPARATION [permalink]
Andrew Nesbit, Electronic Engineering & Computer Science, Queen Mary, University of London, United Kingdom, Emmanuel Vincent, METISS Group, IRISA-INRIA, Campus de Beaulieu, 35042 Rennes Cedex, France, Mark D. Plumbley, Electronic Engineering & Computer Science, Queen Mary, University of London, United Kingdom (2009)
BESPOKE NEURAL NETWORKS FOR SCORE-INFORMED SOURCE SEPARATION [PDF]
Ethan Manilow, Bryan Pardo, Interactive Audio Lab Northwestern University, Evanston, Illinois, USA (2020)
BETA DIVERGENCE FOR CLUSTERING IN MONAURAL BLIND SOURCE SEPARATION [permalink]
Martin Spiertz, Volke Gnann, Institut für Nachrichtentechnik, RWTH Aachen University, Aachen, Germany (2010)
BETA PROCESS SPARSE NONNEGATIVE MATRIX FACTORIZATION FOR MUSIC [PDF]
Dawen Liang and Daniel P. W. Ellis, LabROSA, EE Dept., Columbia University, Matthew D. Hoffman, Adobe Research, Adobe Systems Incorporated (2013)
BEYOND NMF: TIME-DOMAIN AUDIO SOURCE SEPARATION WITHOUT PHASE RECONSTRUCTION [PDF]
Kazuyoshi Yoshii1, Ryota Tomioka2, Daichi Mochihashi3, Masataka Goto1, 1National Institute of Advanced Industrial Science and Technology (AIST), 2The University of Tokyo, 3The Institute of Statistical Mathematics (ISM) (2013)
BEYOND NMF: TIME-DOMAIN AUDIO SOURCE SEPARATION WITHOUT PHASE RECONSTRUCTION (slides) [PDF]
Kazuyoshi Yoshii (AIST, Japan), Ryota Tomioka (Univ. of Tokyo , Japan), Daichi Mochihashi (ISM , Japan), Masataka Goto (AIST , Japan) (2013)
BIO-MIMETIC ATTENTIONAL FEEDBACK IN MUSIC SOURCE SEPARATION [permalink]
Ashwin Bellur, Mounya Elhilali, Johns Hopkins University, Laboratory for Computational Audio Perception (2020)
BITWISE NEURAL NETWORKS FOR EFFICIENT SINGLE-CHANNEL SOURCE SEPARATION [PDF]
Mine Kim, Indiana University, Department of Intelligent Systems Engineering, Paris Smaragdis, University of Illinois at Urbana-Champaign, Adobe Research (2018)
BLIND HARMONIC ADAPTIVE DECOMPOSITION APPLIED TO SUPERVISED SOURCE SEPARATION [PDF]
Benoit Fuentes, Roland Badeau, Gaël Richard, Institut Mines-Télécom, Télécom ParisTech, Paris, France (2012)
BLIND AUDIO SOURCE SEPARATION [PDF]
Emmanuel Vincent, Maria G. Jafari, Samer A. Abdallah, Mark D. Plumbley, Mike E. Davies, Centre For Digital Music, Queen Mary University of London (2005)
BLIND AUDIO SOURCE SEPARATION [PDF]
Vincent Yan Fu Tan (SID), Signal Processing Laboratory, Department of Engineering, University of Cambridge (2005)
BLIND AUDIO SOURCE SEPARATION: A REVIEW OF STATE-OF-THE-ART TECHNIQUES (slides) [PDF]
Emmanuel Vincent, Centre for Digital Music, Electronic Engineering Department, Queen Mary, University of London (2005)
BLIND AUDIO SOURCE SEPARATION PIPELINE AND ALGORITHM EVALUATION [PDF]
Wisam Reid, Kai-Chieh Huang & Doron Roberts-Kedes, Stanford University, Stanford, California, USA (2015)
BLIND AUDIO SOURCE SEPARATION USING SHORT+LONG TERM AR SOURCE MODELS AND ITERATIVE ITAKURA-SAITO DISTANCE MINIMIZATION [permalink]
Antony Schutz and Dirk Slock, EURECOM, Mobile Communications Dept., Sophia Antipolis Cedex, France (2011)
BLIND AUDIO SOURCE SEPARATION WITH MINIMUM-VOLUME BETA-DIVERGENCE NMF [PDF]
Valentin Leplat, Nicolas Gillis, Man Shun Ang, Department of Mathematics and Operational Research, Faculté Polytechnique, Université de Mons, Mons, Belgium (2019)
BLIND DECOMPOSITION OF CONCURRENT SOUNDS [PDF]
Mamoru Ueda, Shuji Hashimoto, Department of Applied Physics of Science and Engineering, Waseda University, Tokyo, Japan (1994)
BLIND HARMONIC ADAPTIVE DECOMPOSITION APPLIED TO SUPERVISED SOURCE SEPARATION [PDF]
Benoit Fuentes, Roland Badeau, Gaël Richard, Institut Mines-Télécom, Paris, France (2012)
BLIND MONAURAL SINGING VOICE SEPARATION USING RANK-1 CONSTRAINT ROBUST PRINCIPAL COMPONENT ANALYSIS AND VOCAL ACTIVITY DETECTION [permalink]
Feng Li, Masato Akagi, Japan Advanced Institute of Science and Technology (JAIST), Nomi, Japan (2019)
BLIND MUSIC TIMBRE SOURCE ISOLATION BY MULTI-RESOLUTION COMPARISON OF SPECTRUM SIGNATURES [PDF]
Xin Zhang1 , Wenxin Jiang2, Zbigniew W. Ras2,4,5, Rory Lewis3, 1 Univ. of North Carolina, Dept. of Math. and Comp. Science, Pembroke, North Carolina, USA 2 Univ. of North Carolina, Dept. of Comp. Science, Charlotte, North Carolina, USA, 3 Univ. of Colorado, Dept. of Comp. Science, Colorado Springs, Colorado, USA 4 Polish-Japanese Institute of Information Technology, Warsaw, Poland, 5 Polish Academy of Sciences, Institute of Comp. Science, Warsaw, Poland (2010)
BLIND ONE-MICROPHONE SPEECH SEPARATION: A SPECTRAL LEARNING APPROACH [PDF]
Francis R. Bach, Computer Science, University of California, Michael I. Jordan, Computer Science and Statistics, University of California (2004)
BLIND RHYTHMIC SOURCE SEPARATION: NONNEGATIVITY AND REPEATABILITY [permalink]
Minje Kim1, Jiho Yoo2, Kyeongok Kang3 and Seungjin Choi4, Electronics and Telecommunications Research Institute (ETRI), Korea1,3 Department of Computer Science, POSTECH, Korea2,4 (2010)
BLIND SEPARATION OF ACOUSTIC SIGNALS USING A NEURAL NETWORK [PDF]
Bernd Freisleben1, Claudia Hagen2, and Markus Borschbach1, 1Department of Electrical Engineering and Computer Science, University of Siegen, Siegen, Germany, 2Department of Computer Science, University of Darmstadt, Darmstadt, Germany (1997)
BLIND SEPARATION OF AUDIO SOURCES USING MODAL DECOMPOSITION [permalink]
A. Aïssa-El-Bey, K. Abed-Meraim, Y. Grenier, ENST-Paris, Paris, France (2005)
BLIND SEPARATION OF OVERLAPPING PARTIALS IN HARMONIC MUSICAL NOTES USING AMPLITUDE AND PHASE RECONSTRUCTION [PDF]
Jesús Ponce de León and José Ramón Beltrán, EURASIP Journal on Advances in Signal Processing (2012)
BLIND SEPARATION OF SINGLE CHANNEL MIXTURE USING ICA BASIS FUNCTIONS [PDF]
Gil-Jin Jang1,2, Te-Won Lee1, and Yung-Hwan Oh2, 1 Institute for Neural Computation, University of California, San Diego, La Jolla, California, USA, 2 Spoken Language Laboratory, Department of Computer Science, Korea Advanced Institute of Science and Technology, Taejon, Korea (2001)
BLIND SIGNAL SEPARATION OF SIMILAR PITCHES AND INSTRUMENTS IN A NOISY POLYPHONIC DOMAIN [PDF]
Rory A. Lewis, Xin Zhang and Zbigniew W. Raś, University of North Carolina, KDD Laboratory, Charlotte, NC (2006)
BLIND SINGLE CHANNEL SOUND SOURCE SEPARATION [PDF]
Mark Leddy, Dublin Institute of Technology (2010)
BLIND SOURCE SEPARATION BASED ON COVARIANCE RATIO AND ARTIFICIAL BEE COLONY ALGORITHM [PDF direct download]
Lei Chen,1 Liyi Zhang,1,2 Yanju Guo,3 Yong Huang,1 and Jingyi Liang1, 1 School of Information Engineering, Tianjin University of Commerce, Tianjin, China, 2 School of Electronic Information Engineering, Tianjin University, Tianjin, China, 3 School of Information Engineering, Hebei University of Technology, Tianjin, China (2014)
BLIND SOURCE SEPARATION IN POLYPHONIC MUSIC RECORDINGS USING DEEP NEURAL NETWORKS TRAINED VIA POLICY GRADIENTS [PDF direct download]
Sören Schulze 1, Johannes Leuschner 1, and Emily J. King 2, 1 Center for Industrial Mathematics, University of Bremen, Bremen, Germany, 2 Mathematics Department, Colorado State University, Fort Collins, Colorado
BLIND SOURCE SEPARATION IN SINGLE-CHANNEL POLYPHONIC MUSIC RECORDINGS [PDF direct download]
Sören Schulze, M. Sc., Universität Bremen, Bremen, Germany (2021)
BLIND SOURCE SEPARATION OF AUDIO SIGNALS USING WVD-KR ALGORITHM [PDF]
D. Sugumar 1, Neethu Susan Rajan 2 & P. T. Vanathi 3, 1,2 ECE Department, Karunya University Coimbatore, India 3 PSG Tech, ECE Department, Coimbatore, India (2013)
BLIND SOURCE SEPARATION OF MONAURAL MUSICAL SIGNALS USING COMPLEX WAVELETS [PDF]
José Ramón Beltrán Blázquez, Jesús Ponce de León Vázquez, Dpt. of Electronic Engineering and Communications, University of Zaragoza, Zaragoza, Spain, Proc. of the 12th Int. Conference on Digital Audio Effects (DAFx-09), Como, Italy (2009)
BLIND SOURCE SEPARATION OF MUSICAL INSTRUMENT SIGNALS BY IDENTIFICATION OF WAVELETS AND FILTER BANK COEFFICIENTS [permalink]
Sinith, M.S. ; Dept. of Electron. & Commun. Eng., Amrita Vishwa Vidyapeetham, Amritapuri, India ; Nair, M.N. ; Nair, N.P. ; Parvathy, S. (2011)
BLIND SOURCE SEPARATION USING REPETITIVE STRUCTURE [PDF]
R. Mitchell Parry and Irfan Essa, College of Computing / GVU Center Georgia Institute of Technology, Atlanta, GA (2005)
BLIND SOURCE SEPARATION USING STATISTICAL NONNEGATIVE MATRIX FACTORIZATION [PDF]
Phetcharat Parathai, Newcastle University, Newcastle upon Tyne, UK (2015)
BLIND SOURCE SEPARATION USING WAVELETS [PDF]
A.Wims Magdalene Mary, Anto Prem Kumar, Anish Abraham Chacko, Karunya University, Coimbatore, India, 2010 IEEE International Conference on Computational Intelligence and Computing Research (2010)
BLIND SOURCE SEPARATION VIA INDEPENDENT COMPONENT ANALYSIS : ALGORITHMS AND APPLICATIONS [PDF]
Jaya Kulchandani, Kruti J. Dangarwala, Department of Information Technology Shri S’ad Vidya Mandal Institute of Technology Bharuch 392-001, Gujarat, India (2014)
BLIND UPMIX FOR APPLAUSE-LIKE SIGNALS BASED ON PERCEPTUAL PLAUSIBILITY CRITERIA [PDF]
Alexander Adami, Lukas Brand, Jürgen Herre, International Audio Laboratories, Friedrich-Alexander Universität Erlangen, Erlangen, Germany, Sascha Disch, Fraunhofer IIS, Erlangen, Germany (2017)
BOOTSTRAPPING DEEP MUSIC SEPARATION FROM PRIMITIVE AUDITORY GROUPING PRINCIPLES [PDF]
Prem Seetharaman1, Gordon Wichern2, Jonathan Le Roux2, Bryan Pardo1, 1Northwestern University, Evanston, IL, USA, 2Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA (2019)
BOOTSTRAPPING SINGLE-CHANNEL SOURCE SEPARATION VIA UNSUPERVISED SPATIAL CLUSTERING ON STEREO MIXTURES [PDF]
Prem Seetharaman1, Gordon Wichern2, Jonathan Le Roux2, Bryan Pardo1, 1Northwestern University, Evanston, IL, USA, 2Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA (2018)
BOOTSTRAPPING THE LEARNING PROCESS FOR COMPUTER AUDITION [PDF]
Prem Seetharaman, Northwestern University, Evanston, Illinois, USA (21019)
BOOTSTRAPPING THE LEARNING PROCESS FOR COMPUTER AUDITION (audio examples)
Prem Seetharaman, Northwestern University, Evanston, Illinois, USA (21019)
BREAKING THE BOUNDS: INTRODUCING INFORMED SPECTRAL ANALYSIS [PDF]
Sylvain Marchand, Dominique Fourer, LaBRI – CNRS University of Bordeaux 1 Talence, France (2010)
BREAKING THE BOUNDS: INTRODUCING INFORMED SPECTRAL ANALYSIS (demo)
Sylvain Marchand, Dominique Fourer, LaBRI – CNRS University of Bordeaux 1 Talence, France (2010)
CASS: CROSS ADVERSARIAL SOURCE SEPARATION VIA AUTOENCODER [PDF]
Yong Zheng Ong, Department of Mathematics, National University of Singapore, Charles Chui, Department of Mathematics, Hong Kong Baptist University, Kowloon, Hong Kong, Haizhao Yang, Department of Mathematics and Institute of Data Science, National University of Singapore (2019)
CATALOG-BASED SINGLE-CHANNEL SPEECH-MUSIC SEPARATION WITH THE ITAKURA-SAITO DIVERGENCE [PDF]
Cemil Demir1,3, A. Taylan Cemgil2, Murat Saraclar3, 1TÜBİTAK-BİLGEM, Kocaeli, Turkey, 2Computer Engineering Department, Boğaziçi University, İstanbul,Turkey, 3Electrical and Electronics Engineering Department, Boğaziçi University, İstanbul,Turkey (2012)
CATNET: MUSIC SOURCE SEPARATION SYSTEM WITH MIX-AUDIO AUGMENTATION [PDF]
Xuchen Song, Qiuqiang Kong, Xingjian Du, Yuxuan Wang, ByteDance, Shanghai, China (2021)
CAUCHY NONNEGATIVE MATRIX FACTORIZATION [PDF]
Antoine Liutkus1 Derry Fitzgerald2 Roland Badeau3, 1Inria, Speech Processing Team, Villers-lès-Nancy, France, 2NIMBUS Centre, Cork Institute of Technology, Ireland, 3Institut Mines-Télécom, Télécom ParisTech, CNRS LTCI, France <hal-01170924> (2015)
CHANNEL-WISE SUBBAND INPUT FOR BETTER VOICE AND ACCOMPANIMENT SEPARATION ON HIGH RESOLUTION MUSIC [PDF]
Haohe Liu, Lei Xie, Jian Wu, Geng Yang, Audio, Speech and Language Processing Group (ASLP@NPU), School of Computer Science, Northwestern Polytechnical University, Xian, China (2020)
CLASS-CONDITIONAL EMBEDDINGS FOR MUSIC SOURCE SEPARATION [PDF]
Prem Seetharaman1,2, Gordon Wichern1, Shrikant Venkataramani1,3, Jonathan Le Roux1, 1Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA, 2Northwestern University, Evanston, IL, USA, 3University of Illinois at Urbana-Champaign, Champaign, IL, USA (2019)
CLASSIFYING NMF COMPONENTS BASED ON VECTOR SIMILARITY FOR SPEECH AND MUSIC SEPARATION [PDF]
Nengheng Zheng*, Yi Cai*, Xia Li* and Tan Lee†, *Shenzhen Key Lab of Telecommunication and Information Processing, College of Information Engineering, Shenzhen University, Shenzhen, China, †Department of Electronic Engineering, Chinese University of Hong Kong, Hong Kong, China (2012)
CLUSTERING ALGORITHM FOR UNSUPERVISED MONAURAL MUSICAL SOUND SEPARATION BASED ON NON-NEGATIVE MATRIX FACTORIZATION [permalink]
Sang Ha Park, Seokjin Lee, Koeng-Mo Sung, INMC, Seoul National University, South Korea (2012)
CLUSTERING NMF BASIS FUNCTIONS USING SHIFTED NMF FOR MONAURAL SOUND SOURCE SEPARATION [PDF]
Rajesh Jaiswal⋆, Derry FitzGerald⋆, Dan Barry⋆, Eugene Coyle⋆, Scott Rickard†, ⋆ Audio Research Group, Dublin Institute of Technology, Dublin, Ireland, †Dept of Electronic Engineering, University College Dublin, Dublin, Ireland (2011)
COCHLEAGRAM-BASED AUDIO PATTERN SEPARATION USING TWO-DIMENSIONAL NON-NEGATIVE MATRIX FACTORIZATION WITH AUTOMATIC SPARSITY ADAPTATION [permalink]
Bin Gao, School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, People's Republic of China, W. L. Woo and L. C. Khor, School of Electrical and Electronic Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom (2014)
COCKTAIL PARTY PROCESSING VIA STRUCTURED PREDICTION [PDF]
Yuxuan Wang1, DeLiang Wang1,2, 1Department of Computer Science and Engineering, 2Center for Cognitive Science, The Ohio State University,
Columbus, Ohio (2012)
CODEBOOK-BASED SINGLE-CHANNEL BLIND SOURCE SEPARATION OF AUDIO SIGNALS [PDF]
Guy Rapaport, Technion-Israel Institute of Technology, Haifa, Israel (2011)
CODING-BASED INFORMED SOURCE SEPARATION: NONEGATIVE TENSOR FACTORIZATION APPROACH [permalink]
Alexey Ozerov, Antoine Liutkus, Roland Badeau, Gaël Richard, IEEE Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers (2013)
COHERENT MODULATION SPECTRAL FILTERING FOR SINGLE-CHANNEL MUSIC SOURCE SEPARATION [permalink]
Les Atlas* and Christiaan Janssen**, *Department of Electrical Engineering, University of Washington Seattle, Washington, USA, **Fraunhofer IIS,
Erlangen, Germany (2005)
COMBINED-CHANNEL INSTANTANEOUS FREQUENCY ANALYSIS FOR AUDIO SOURCE SEPARATION BASED ON COMODULATION [permalink]
Barry David Jacobson, Massachusetts Intitute of Technology (2008)
COMBINING A HARMONIC-BASED NMF DECOMPOSITION WITH TRANSIENT ANALYSIS FOR INSTANTANEOUS PERCUSSION SEPARATION [PDF]
Jordi Janer, Ricard Marxer, Music Technology Group, Universitat Pompeu Fabra, Barcelona, Spain, Keita Arimoto, Yamaha Corp., Japan (2012)
COMBINING FULLY CONVOLUTIONAL AND RECURRENT NEURAL NETWORKS FOR SINGLE CHANNEL AUDIO SOURCE SEPARATION [permalink]
Emad M. Grais, Mark D. Plumbley, University of Surrey, Guildford, Surrey, UK (2018)
COMBINING HMM-BASED MELODY EXTRACTION AND NMF-BASED SOFT MASKING FOR SEPARATING VOICE AND ACCOMPANIMENT FROM MONAURAL AUDIO [permalink]
Yun Wang, Zhijian Ou, Department of Electronic Engineering, Tsinghua University, Beijing, China (2011)
Yun Wang (Maigo), Zhijian Ou, Department of Electronic Engineering, Tsinghua University, Beijing, China
COMBINING MASK ESTIMATES FOR SINGLE CHANNEL AUDIO SOURCE SEPARATION USING DEEP NEURAL NETWORKS [PDF]
Emad M. Grais, Gerard Roma, Andrew J.R. Simpson, Mark D. Plumbley, Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, UK (2016)
COMBINING MODELING OF SINGING VOICE AND BACKGROUND MUSIC FOR AUTOMATIC SEPARATION OF MUSICAL MIXTURES [PDF]
Zafar Rafii1, François G. Germain2, Dennis L. Sun2,3, and Gautham J. Mysore4, 1Northwestern University, Department of Electrical Engineering & Computer Science 2Stanford University, Center for Computer Research in Music and Acoustics 3Stanford University, Department of Statistics, 4Adobe Research (2013)
COMBINING MODELING OF SINGING VOICE AND BACKGROUND MUSIC FOR AUTOMATIC SEPARATION OF MUSICAL MIXTURES (poster) [PDF]
Zafar Rafii1, François G. Germain2, Dennis L. Sun2,3, and Gautham J. Mysore4, 1Northwestern University, Department of Electrical Engineering & Computer Science 2Stanford University, Center for Computer Research in Music and Acoustics 3Stanford University, Department of Statistics, 4Adobe Research (2013)
COMBINING PITCH-BASED INFERENCE AND NON-NEGATIVE SPECTROGRAM FACTORIZATION IN SEPARATING VOCALS FROM POLYPHONIC MUSIC [PDF]
Tuomas Virtanen, Annamaria Mesaros, Matti Ryynänen, Department of Signal Processing, Tampere University of Technology, Finland (2008)
COMBINING RHYTHM-BASED AND PITCH-BASED METHODS FOR BACKGROUND AND MELODY SEPARATION [permalink]
Zafar Rafii, Bryan Pardo, Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, Illinois, USA, Zhiyao Duan, Department of Electrical and Computer Engineering, University of Rochester, Rochester, New York, USA (2014)
COMMON FATE MODEL FOR UNISON SOURCE SEPARATION [PDF]
Fabian-Robert Stöter⋆, Antoine Liutkus†, Roland Badeau‡, Bernd Edler⋆, Paul Magron‡, ⋆ International Audio Laboratories Erlangen∗, † Inria, speech processing team, Villers-les-Nancy, France, ‡ Institut Mines-Télécom, Télécom ParisTech, CNRS LTCI, France <hal- 01248012> (2016)
COMPARISON OF EFFECTIVENESS OF MUSICAL SOUND SEPARATION ALGORITHMS EMPLOYING NEURAL NETWORKS [permalink]
Piotr Dalka, Marek Dziubinski, Bozena Kostek, Multimedia Systems Department, Gdańsk University of Technology, Gdańsk, Poland (2004)
COMPARISON OF SEVERAL METHODS FOR SEPARATION OF HARMONIC AND NOISE COMPONENTS OF MUSICAL INSTRUMENT SOUND [PDF]
Ondřej Moravec, Faculty of Music of the Academy of Performing Arts in Prague, Prague, Czech Republic (2002)
COMPARISON OF THE QUALITY OF PERCUSSIVE AND NON-PERCUSSIVE SOUNDS SEPARATED FROM A MIXTURE OF INSTRUMENTAL SOUNDS [PDF]
Alpana Gupta1, Jaswinder Singh2, Praveen Lehana3, 1M.Tech Student, Punjab Technical University, India, 2Dept. of Electronics and Communication Engg, BCET Gurdaspur, India 3Dept. of Physics and Electronics, University of Jammu, India (2014)
COMPARATIVE EVALUATIONS OF VARIOUS HARMONIC/PERCUSSIVE SOUND SEPARATION ALGORITHMS BASED ON ANISOTROPIC CONTINUITY OF SPECTROGRAM [permalink]
Hideyuki Tachibana1, Hirokazu Kameoka1,2, Nobutaka Ono3, Shigeki Sagayama1, 1Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan, 2NTT Communication Science Laboratories, NTT Corporation, Kanagawa, Japan, 3National Institute of Informatics, Tokyo, Japan (2012)
COMPARITIVE STUDY OF FILTER PERFORMANCE FOR SEPARATION OF SINGING VOICE FROM MUSIC ACCOMPANIMENT [PDF]
Harshada P. Burute1, Madhuri Patil2, Kirtimalini Chaudhari3, Dr. Pradeep B. Mane4, Department of Electronics, All India Shri Shivaji Memorial Society, Institute of Information Technology, Pune, Maharashtra, India1,4, Department of Electronics, All India Shri Shivaji Memorial Society, College of Engineering, Pune, Maharashtra, India2,3 (2015)
COMPLEX AND QUATERNIONIC PRINCIPAL COMPONENT PURSUIT AND ITS APPLICATION TO AUDIO SEPARATION [permalink]
Tak-Shing T. Chan and Yi-Hsuan Yang, Research Center for Information Technology Innovation, Academia Sinica, Taipei, Taiwan (2016)
COMPLEX ISNMF: A PHASE-AWARE MODEL FOR MONAURAL AUDIO SOURCE SEPARATION [PDF]
Paul Magron, Tuomas Virtanen, Member, IEEE, Laboratory of Signal Processing, Tampere University of Technology, Finland (2018)
COMPLEX NMF UNDER PHASE CONSTRAINTS BASED ON SIGNAL MODELING: APPLICATION TO AUDIO SOURCE SEPARATION [PDF]
Paul Magron, Roland Badeau, Bertrand David, LTCI, CNRS, Télécom ParisTech, Université Paris-Saclay, 75013, Paris, France (2016)
COMPLEX RATIO MASKING FOR SINGING VOICE SEPARATION [PDF]
Yixuan Zhang1, Yuzhou Liu1 and DeLiang Wang1,2, 1Department of Computer Science and Engineering, The Ohio State University, USA, 2Center for Cognitive and Brain Sciences, The Ohio State University, USA (2020)
COMPLEX SVD INITIALIZATION FOR NMF SOURCE SEPARATION ON AUDIO SPECTROGRAMS [PDF]
Julian Becker1, Matthias Menzel1, Christian Rohlfing1, 1 Institut für Nachrichtentechnik, RWTH Aachen, 52056 Aachen, Deutschland (2015)
COMPLEX-VALUED DEEP RECURRENT NEURAL NETWORK FOR SINGING VOICE SEPARATION (in Chinese) [permalink]
Kuo Yu, National Central University, Taiwan
COMPONENT-ADAPTIVE PRIORS FOR NMF [PDF]
Julian M. Becker and Christian Rohlfing, Institut für Nachrichtentechnik, RWTH Aachen University, Aachen, Germany (2015)
COMPOSITIONAL MODELS FOR AUDIO PROCESSING: UNCOVERING THE STRUCTURE OF SOUND MIXTURES [permalink]
Tuomas Virtanen, Jort F. Gemmeke, Bhiksha Raj, Paris Smaragdis, Dept. of Signal Process., Tampere Univ. of Technol., Tampere, Finland (2015)
COMPRESSED SENSING AND SOURCE SEPARATION [PDF]
Thomas Blumensath and Mike Davies, IDCOM & Joint Research Institute for Signal and Image Processing, The University of Edinburgh, Edinburgh, UK (2007)
COMPRESSIVE SAMPLING-BASED INFORMED SOURCE SEPARATION [permalink]
Çağdaş Bilen, Alexey Ozerov, Patrick Pérez, Technicolor, Cesson Sévigné, France (2015)
COMPUTATIONAL AUDITORY SCENE ANALYSIS, PART 1: AN INTRODUCTION TO TIME–FREQUENCY MASKING
Chris Hummersone, Institute of Sound Recording Blog, University of Surrey, Guildford, Surrey, United Kingdom (2013)
COMPUTATIONAL AUDITORY SCENE ANALYSIS, PART 2: TIME–FREQUENCY MASKING: BINARY OR NOT?
Chris Hummersone, Institute of Sound Recording Blog, University of Surrey, Guildford, Surrey, United Kingdom (2013)
COMPUTATIONALLY MEASURABLE TEMPORAL DIFFERENCES BETWEEN SPEECH AND SONG [PDF]
David Bruce Gerhard, University of Manitoba (2003)
COMPUTATIONAL MUSIC AUDIO SCENE ANALYSIS [PDF]
Zhiyao Duan, Northwestern University, Evanston, Illinois (2013)
COMPUTE AND MEMORY EFFICIENT UNIVERSAL SOUND SOURCE SEPARATION [permalink]
Efthymios Tzinis, Zhepei Wang, Xilin Jiang, University of Illinois at Urbana-Champaign, Champaign, IL, USA, Paris Smaragdis, University of Illinois at Urbana-Champaign, Adobe Research, Champaign, IL, USA (2022)
CONDITIONED SOURCE SEPARATION BY ATTENTIVELY AGGREGATING FREQUENCY TRANSFORMATIONS WITH SELF-CONDITIONING [PDF]
WOOSUNG CHOI1, YEONG-SEOK JEONG1, JINSUNG KIM1, JAEHWA CHUNG2, SOONYOUNG JUNG1, AND JOSHUA D. REISS3 ∗ AES Fellow, 1Department of Computer Science and Engineering, Korea University, Republic of Korea, 2Department of Computer Science, Korea National Open University, Republic of Korea, 3Centre for Digital Music, Queen Mary University of London, London, UK (2022)
CONDITIONED SOURCE SEPARATION FOR MUSIC INSTRUMENT PERFORMANCES (project page)
Olga Slizovskaia & Gloria Haro, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain, Emilia Gómez, Centre for Advanced Studies, Joint Research Centre, European Commission, Seville, Spain, Department of In- formation and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain (2020)
CONDITIONED SOURCE SEPARATION FOR MUSIC INSTRUMENT PERFORMANCES [PDF]
Olga Slizovskaia & Gloria Haro, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain, Emilia Gómez, Centre for Advanced Studies, Joint Research Centre, European Commission, Seville, Spain, Department of In- formation and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain (2020)
CONDITIONED-U-NET: INTRODUCING A CONTROL MECHANISM IN THE U-NET FOR MULTIPLE SOURCE SEPARATIONS [PDF]
Gabriel Meseguer-Brocal, Ircam Lab, CNRS, Sorbonne Université, Paris, France, Geoffroy Peeters, LTCI, Télécom Paris, Institut Polytechnique de Paris, Paris, France (2019)
CONSISTENT AND RELEVANT: RETHINK THE QUERY EMBEDDING IN GENERAL SOUND SEPARATION [PDF]
Yuanyuan Wang1,∗, Hangting Chen2, Dongchao Yang3, Jianwei Yu2, Chao Weng2, Zhiyong Wu1,3,†, Helen Meng3, 1 Shenzhen International Graduate School, Tsinghua University, Shenzhen, China, 2 Tencent AI Lab, Audio and Speech Signal Processing Oteam, China, 3 The Chinese University of Hong Kong, Hong Kong SAR, China (2023)
CONSISTENT ANISOTROPIC WIENER FILTERING FOR AUDIO SOURCE SEPARATION [PDF]
Paul Magron,1∗ Jonathan Le Roux,2 Tuomas Virtanen,1, 1 Signal Processing Laboratory, Tampere University of Technology (TUT), Finland, 2 Mitsubishi Electric Research Laboratories (MERL), Cambridge, Massachusetts (2017)
CONSTRAINED AND REGULARIZED VARIANTS OF NON-NEGATIVE MATRIX FACTORIZATION INCORPORATING MUSIC-SPECIFIC CONSTRAINTS [permalink]
Hirokazu Kameoka1,2, Masahiro Nakano2, Kazuki Ochiai1, Yutaka Imoto1, Kunio Kashino2, Shigeki Sagayama1, 1 Graduate School of Information Science and Technology, The University of Tokyo 2 NTT Communication Science Laboratories, NTT Corporation (2012)
CONSTRAINED EM ESTIMATES FOR HARMONIC SOURCE SEPARATION [permalink]
Pamornpol Jinachitra, Center for Computer Research in Music and Acoustics, Stanford University, Stanford, California, USA (2003)
CONSTRAINED TIME-VARIANT SIGNAL MODELING FOR IDENTIFYING COLLIDING HARMONICS IN SOUND MIXTURES [PDF]
Miroslav Zivanovic1 and Johan Schoukens2, 1Dpt. IEE, Universidad Publica de Navarra, Campus Arrosadia,Pamplona, Spain, 2Dpt. ELEC, Vrije Universiteit Brussel, Brussels, Belgium (2011)
CONTENT BASED SINGING VOICE EXTRACTION FROM A MUSICAL MIXTURE [PDF]
Pritish Chandna1, Merlijn Blaauw1, Jordi Bonada1, Emilia Gómez1,2, 1Music Technology Group, Universitat Pompeu Fabra, Barcelona, Spain, 2Joint Research Centre, European Commission, Seville, Spain (2020)
CONTENT BASED SINGING VOICE SOURCE SEPARATION VIA STRONG CONDITIONING USING ALIGNED PHONEMES [PDF]
Gabriel Meseguer-Brocal, STMS UMR9912, Ircam/CNRS/SU, Paris, Geoffroy Peeters, LTCI, Institut Polytechnique de Paris (2020)
CONTRASTIVE LEARNING BASED DEEP LATENT MASKING FOR MUSIC SOURCE SEPARATION [PDF]
Jihyun Kim1, Hong-Goo Kang1, 1Department of Electrical and Electronic Engineering, Yonsei University, South Korea (2023)
CONTRIBUTIONS IN AUDIO MODELING FOR SOLVING INVERSE PROBLEMS: SOURCE SEPARATION, COMPRESSION AND INPAINTING [PDF]
Alexey Ozerov, Université Rennes (2019)
CONTRIBUTIONS TO AUDIO SOURCE SEPARATION AND CONTENT DESCRIPTION [PDF]
Emmanuel Vincent, Université Rennes 1, Rennes, France <tel-00758517v2> (2012)
CONVOLUTIONAL AUDIO SOURCE SEPARATION APPLIED TO DRUM SIGNAL SEPARATION [PDF]
Marius Orehovschi, Colby College, Waterville, Maine, USA (2021)
CONVOLUTIONAL SPARSE CODING BASED SOURCE SEPARATION (separation results)
Ping-Keng Jao, Yi-Hsuan Yang and Brendt Wohlberg (2015)
CONVOLUTIONAL VS. RECURRENT NEURAL NETWORKS FOR AUDIO SOURCE SEPARATION [PDF]
Shariq Mobin * 1 2, Brian Cheung * 1 2, Bruno Olshausen 1 2, *Equal contribution, 1Redwood Center for Theoretical Neuro-science, 2University of California Berkeley (2018)
CONVOLUTIVE NON-NEGATIVE MATRIX FACTORIZATION FOR CQT TRANSFORM USING ITAKURA-SAITO DIVERGENCE [PDF]
Fabio Louvatti do Carmo; Evandro Ottoni Teatini Salles, Federal University of Espirito Santo (UFES), Vitoria-ES, Brazil (2017)
CORRELATED MODULATION: A CRITERION FOR BLIND SOURCE SEPARATION [PS]
Jörn Anemüller, Medical Physics Group and Graduate School in Psychoacoustics, Carl von Ossietzky-University, Oldenburg, Germany (1999)
CORRELATED TENSOR FACTORIZATION FOR AUDIO SOURCE SEPARATION [PDF]
Kazuyoshi Yoshii, Graduate School of Informatics, Kyoto University, Japan RIKEN Center for Advanced Intelligence Project (AIP), Japan (2018)
CORRELATED TENSOR FACTORIZATION FOR AUDIO SOURCE SEPARATION (poster) [PDF]
Kazuyoshi Yoshii, Kyoto University/RIKEN AIP (2018)
CORRELATION-BASED AMPLITUDE ESTIMATION OF COINCIDENT PARTIALS IN MONAURAL MUSICAL SIGNALS [PDF]
Jayme Garcia Arnal Barbedo1 and George Tzanetakis2, 1 Department of Communications, FEEC, Campinas, SP, Brazil 2 Department of Computer Science, University of Victoria, Columbia, Canada (2010)
COVARIANCE SMOOTHING AND CONSISTENT WIENER FILTERING FOR ARTIFACT REDUCTION IN AUDIO SOURCE SEPARATION (slides) [PDF]
Emmanuel Vincent, METISS Team, Inria Rennes - Bretagne Atlantique (2012)
CREPE: A CONVOLUTIONAL REPRESENTATION FOR PITCH ESTIMATION [PDF]
Jong Wook Kim1, Justin Salamon1,2, Peter Li1, Juan Pablo Bello1, 1Music and Audio Research Laboratory, New York University, 2Center for Urban Science and Progress, New York University (2018)
CREPE: A CONVOLUTIONAL REPRESENTATION FOR PITCH ESTIMATION (slides) [PDF]
Jong Wook Kim, Justin Salamon, Peter Li, Juan Pablo Bello Music and Audio Research Laboratory, New York University (2018)
CS230 - AUDIO SEPARATION AND ISOLATION: A DEEP NEURAL NETWORK APPROACH [PDF]
Ahmed Hamdy, Pratap Kiran Vedula, Muni Venkata, Jasantha Konduru, Stanford University, Stanford, California, USA (2019)
CS230 - AUDIO SEPARATION AND ISOLATION: A DEEP NEURAL NETWORK APPROACH (video presentation)
Ahmed Hamdy, Pratap Kiran Vedula, Muni Venkata, Jasantha Konduru, Stanford University, Stanford, California, USA (2019)
CURRENT TRENDS IN AUDIO SOURCE SEPARATION (video)
Fabian-Robert Stöter, Inria, Stefan Uhlich, Sony (2020)
CUSTOM SIZED NON-NEGATIVE MATRIX FACTOR DECONVOLUTION FOR SOUND SOURCE SEPARATION [PDF]
Julian M. Becker and Christian Rohlfing, Institut für Nachrichtentechnik, RWTH Aachen University, Aachen, Germany (2014)
CUTTING MUSIC SOURCE SEPARATION SOME SLAKH: A DATASET TO STUDY THE IMPACT OF TRAINING DATA QUALITY AND QUANTITY [PDF]
Ethan Manilow1,2, Gordon Wichern1, Prem Seetharaman2, Jonathan Le Roux1, 1Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA, 2Interactive Audio Lab, Northwestern University, Evanston, IL, USA (2019)
CWS-PRESUNET: MUSIC SOURCE SEPARATION WITH CHANNEL-WISE SUBBAND PHASE-AWARE RESUNET [PDF]
Haohe Liu1, 2, Qiuqiang Kong1, and Jiafeng Liu1, 1 Sound, Audio, and Music Intelligence (SAMI) Group, ByteDance 2 The Ohio State University (2021)
CYCLE GAN-BASED AUDIO SOURCE SEPARATION USING TIME–FREQUENCY MASKING [permalink]
Sujo Joseph & Rajeev Rajan (2022)