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RESEARCH [M-MO]

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!

 

MACHINE LEARNING AND ITS APPLICATIONS TO MUSIC [PDF]

Anders Øland, IT University of Copenhagen, Copenhagen, Denmark (2011)

 

MACHINE LEARNING IN LINUX: DEMUCS – MUSIC SOURCE SEPARATION​

Steve Emms, LinuxLinks (2023)

MACHINE LEARNING SOURCE SEPARATION USING MAXIMUM A POSTERIORI NONNEGATIVE MATRIX FACTORIZATION [permalink]

Bin Gao, Sch. of Autom. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China, W. L. Woo, Sch. of Electr. & Electron. Eng., Newcastle Univ., Newcastle upon Tyne, UK, Bingo W-K Ling, Fac. of Eng., Guangdong Univ. of Technol., Guangzhou, China (2013)

MAD TWINNET: MASKER-DENOISER ARCHITECTURE WITH TWIN NETWORKS FOR MONAURAL SOUND SOURCE SEPARATION [PDF]

Konstantinos Drossos†, Stylianos Ioannis Mimilakis∗, Dmitriy Serdyuk‡, Gerald Schuller∗, Tuomas Virtanen†, Yoshua Bengio‡§, †Tampere University of Technology, Tampere, Finland, ∗Fraunhofer IDMT – Technical University of Ilmenau, Ilmenau, Germany, ‡MILA, Université de Montréal, Montreal, Canada, §CIFAR Senior Fellow (2018)

MAD TWINNET: MASKER-DENOISER ARCHITECTURE WITH TWIN NETWORKS FOR MONAURAL SOUND SOURCE SEPARATION (code)

Konstantinos Drossos†, Stylianos Ioannis Mimilakis∗, Dmitriy Serdyuk‡, Gerald Schuller∗, Tuomas Virtanen†, Yoshua Bengio‡§, †Tampere University of Technology, Tampere, Finland, ∗Fraunhofer IDMT – Technical University of Ilmenau, Ilmenau, Germany, ‡MILA, Université de Montréal, Montreal, Canada, §CIFAR Senior Fellow (2018)

MAD TWINNET ON-LINE DEMO

Konstantinos Drossos†, Stylianos Ioannis Mimilakis∗, Dmitriy Serdyuk‡, Gerald Schuller∗, Tuomas Virtanen†, Yoshua Bengio‡§, †Tampere University of Technology, Tampere, Finland, ∗Fraunhofer IDMT – Technical University of Ilmenau, Ilmenau, Germany, ‡MILA, Université de Montréal, Montreal, Canada, §CIFAR Senior Fellow (2018)

MAJORIZATION-MINIMIZATION ALGORITHM FOR SMOOTH ITAKURA-SAITO NONNEGATIVE MATRIX FACTORIZATION [permalink]

Cédric Févotte, CNRS LTCI, Telecom ParisTech, Paris, France (2011)

 

MAJORIZATION-MINIMIZATION ALGORITHM FOR SMOOTH ITAKURA-SAITO NONNEGATIVE MATRIX FACTORIZATION: ICASSP'2011 COMPANION PAGE

Cédric Févotte (2011)

MASK OPTIMIZATION FOR NEURAL NETWORK MONAURAL SOURCE SEPARATION [PDF]

Richard Cant, Caroline Langensiepen, William Metcalfe, School of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom (2017)

MASKS IN SOUND SOURCE SEPARATION: AN ABLATION

Juan F. Montesinos, Pompeu Fabra University (2021)

MASTER'S THESIS – A CAPPELLA SOUND SEPARATION

Kiran Kumar, New York University (2016)

MAXIMUM LIKELIHOOD STUDY FOR SOUND PATTERN SEPARATION AND RECOGNITION [PDF direct download]

Xin Zhang, Krzysztof Marasek, Zbigniew W. Ras, Computer Science Department, University of North Carolina, Charlotte, N.C., USA Multimedia Department, Polish-Japanese Institute of IT, Warsaw, Poland (2007)

 

MEDLEYVOX: AN EVALUATION DATASET FOR MULTIPLE SINGING VOICES SEPARATION [PDF]

Chang-Bin Jeon1*,2, Hyeongi Moon1, Keunwoo Choi1, Ben Sangbae Chon1, Kyogu Lee2, 1Gaudio Lab, Inc., Seoul, South Korea, 2Department of Intelligence and Information, Music and Audio Research Group (MARG), Seoul National University, Seoul, South Korea (2022)

MEL-BAND ROFORMER FOR MUSIC SOURCE SEPARATION [PDF]

Ju-Chiang Wang, Wei-Tsung Lu, Minz Won, Speech, Audio, and Music Intelligence (SAMI), ByteDance (2023)

MELODY EXTRACTION BASED ON HARMONIC CODED STRUCTURE [PDF]

Sihyun Joo, Sanghun Park, Seokhwan Jo, Chang D. Yoo, Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Yuseong-gu, Daejeon, Korea (2011)

 

MELODY EXTRACTION FROM MUSIC

Justin Salamon, Music and Audio Research Laboratory (MARL) and Center for Urban Science and Progress (CUSP) of New York University, Emilia Gómez, Music Technology Group (MTG), Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Daniel P.W. Ellis, Electrical Engineering Department, Columbia University, New York, Gaël Richard, Institut TELECOM, Télécom ParisTech, CNRS-LTCI (2015)

MELODY EXTRACTION FROM POLYPHONIC MUSIC SIGNALS (slides) [PDF]

Gaël Richard, Institut Mines-Telecom, Telecom ParisTech, CNRS LTCI, France (2014)

 

MELODY EXTRACTION FROM POLYPHONIC MUSIC SIGNALS USING PITCH CONTOUR CHARACTERISTICS [permalink]

Justin Salamon, Emilia Gómez, Music Technology Group (MTG) of the Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain (2012)

 

MELODY LINE DETECTION AND SOURCE SEPARATION IN CLASSICAL SAXOPHONE RECORDINGS [PDF]

Estefanía Cano C.(*)(+), Corey Cheng (+)(#), (*)TU Ilmenau/ Fraunhofer Institute IDMT, Ilmenau, Germany, (+)Music Engineering Technology Program Frost School of Music, University of Miami,Coral Gables, Florida, USA, (#)Department of Electrical and Computer Engineering, University of Miami, Coral Gables, Florida, USA (2009)

 

MELODY LINE ESTIMATION IN HOMOPHONIC MUSIC AUDIO SIGNALS BASED ON TEMPORAL-VARIABILITY OF MELODIC SOURCE [permalink]

Hideyuki Tachibana, Takuma Ono, Nobutaka Ono, Shigeki Sagayama, Graduate School of Information Science and Technology, The University of Tokyo, Bunkyo, Tokyo, Japan (2010)

MEMORY AUGMENTED NEURAL NETWORK FOR SOURCE SEPARATION [permalink]

Kai-Wei Tsou, Jen-Tzung Chien, Department of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan (2017)

META-LEARNING EXTRACTORS FOR MUSIC SOURCE SEPARATION [PDF]

David Samuel, Charles University, Prague, Czech Republic, Aditya Ganeshan, Jason Naradowsky, Preferred Networks Tokyo (2020)

META-LEARNING EXTRACTORS FOR MUSIC SOURCE SEPARATION (interactive demo)

David Samuel, Charles University, Prague, Czech Republic, Aditya Ganeshan, Jason Naradowsky, Preferred Networks Tokyo (2020)

META-TASNET: SUMMARY OF AN ICASSP 2020 PAPER ABOUT MUSICAL SOURCE SEPARATION

Kilian Schulze-Forster, MIP-Frontiers (2020)

MÉTHODE STRUCTURÉE DE DÉCOMPOSITION EN MATRICES NON-NÉGATIVES APPLIQUÉÈ A LA SÉPARATION DE SOURCES AUDIO (in French) [PDF]

Clément Laroche1,2, Matthieu Kowalski2,3, Hélène Papadopoulos2, Gaël Richard1, 1Institut Mines-Telecom, Telecom ParisTech, CNRS-LTCI, France, 2Univ Paris-Sud-CNRS-CentraleSupelec, L2S, France, 3Parietal project-team, INRIA, CEA-Saclay, France <hal-01199648> (2015)

METHODS FOR MULTIPLE PITCH TRACKING AND INSTRUMENT SEPARATION FROM MONAURAL POLYPHONIC RECORDINGS [PDF]

Mert Bay, University of Illinois at Urbana-Champaign, Urbana, Illinois (2012)

 

METHODS FOR SEPARATING HARMONIC INSTRUMENTS FROM A MONAURAL MIX [PDF]

Mert Bay, James W. Beauchamp, School of Music and Dept. of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois (2014)

 

METHODS FOR SEPARATION OF HARMONIC SOUND SOURCES USING SINUSOIDAL MODELING [PDF]

Tero Tolonen, Helsinki University of Technology, Laboratory of Acoustics and Audio Signal Processing, Espoo, Finland (2000)

 

METHODS OF SINGLE-CHANNEL MUSIC SOURCE SEPARATION [PDF]

Matthew J. Crossley, University of California, Santa Barbara (2010)

 

MID-LEVEL AUDIO FEATURES BASED ON CASCADED HARMONIC-RESIDUAL-PERCUSSIVE SEPARATION

International Audio Laboratories, Erlangen, Friedrich-Alexander-Universität (FAU), Erlangen, Germany (2017)

MID-LEVEL AUDIO FEATURES BASED ON CASCADED HARMONIC-RESIDUAL-PERCUSSIVE SEPARATION [permalink]

Patricio López-Serrano, Christian Dietmar, Meinard Müller, International Audio Laboratories, Erlangen, Friedrich-Alexander-Universität (FAU), Erlangen, Germany (2017)

MINUET: MUSICAL INTERFERENCE UNMIXING ESTIMATION TECHNIQUE [PDF]

Scott Rickard, Conor Fearon, University College Dublin, Dublin, Ireland, Radu Balan, Justinian Rosca, Siemens Corporate Research, Princeton, New Jersey, USA (2004)

 

MIR-1K DATASET

Chao-Ling Hsu and Prof. Jyh-Shing Roger JangNational Taiwan University Department of Computer Science Multimedia Information Retrieval Lab (2009)

 

MIREX 2014: SINGING VOICE SEPARATION [PDF]

Yukara Ikemiya, Kazuyoshi Yoshii, Katsutoshi Itoyama, Department of Intelligence Science and Technology Graduate School of Informatics, Kyoto University (2014)

 

MIREX 2014: SINGING VOICE SEPARATION RESULTS

(2014)

 

MIREX 2015: SINGING VOICE SEPARATION RESULTS

(2015)

MIREX 2016: SINGING VOICE SEPARATION RESULTS

(2016)

MISSING DATA IMPUTATION FOR SPECTRAL AUDIO SIGNALS [PDF]

Paris Smaragdis, Adobe Systems, Newton, MA, USA, Bhiksha Raj, Carnegie Mellon University, Pittsburgh, PA, USA, Madhusudana Shashanka, Mars Inc., Hackettstown, NJ, USA (2009)

 

MIXING-SPECIFIC DATA AUGMENTATION TECHNIQUES FOR IMPROVED BLIND VIOLIN/PIANO SOURCE SEPARATION [PDF]

Ching-Yu Chiu, Graduate Program of Multimedia Systems and Intelligent Computing, National Cheng Kung University and Academia Sinica, Taiwan,

Wen-Yi Hsiao, Yating Music Team, Taiwan AI Labs, Taiwan, Yin-Cheng Yeh, Yating Music Team, Taiwan AI Labs, Taiwan, Yi-Hsuan Yang, Research Center for IT Innovation, Academia Sinica, Taiwan, Alvin Wen-Yu Su, Dept. CSIE, National Cheng Kung University, Taiwan (2020)

MIXING-SPECIFIC DATA AUGMENTATION TECHNIQUES FOR IMPROVED BLIND VIOLIN/PIANO SOURCE SEPARATION (demo page)

Ching-Yu Chiu, Graduate Program of Multimedia Systems and Intelligent Computing, National Cheng Kung University and Academia Sinica, Taiwan,

Wen-Yi Hsiao, Yating Music Team, Taiwan AI Labs, Taiwan, Yin-Cheng Yeh, Yating Music Team, Taiwan AI Labs, Taiwan, Yi-Hsuan Yang, Research Center for IT Innovation, Academia Sinica, Taiwan, Alvin Wen-Yu Su, Dept. CSIE, National Cheng Kung University, Taiwan (2020)

MLJEJUCAMP2017 - MARK KWON : MONAURAL SOURCE SEPARATION (video)

Mark Kwon (2017)

MMDENSELSTM: AN EFFICIENT COMBINATION OF CONVOLUTIONAL AND RECURRENT NEURAL NETWORKS FOR AUDIO SOURCE SEPARATION [PDF]

Naoya Takahashi1, Nabarun Goswami2, Yuki Mitsufuji1, 1Sony Corporation, Minato-ku, Tokyo, Japan, 2Sony India Software Centre, Bangalore, India (2018)

MODEL-BASED APPROACH TO SEPARATING INSTRUMENTAL MUSIC FROM SINGLE TRACK RECORDINGS [permalink]

Sintiani D. Teddy and Edmund M-K. Lai, School of Computer Engineering, Nanyang Technological University, Singapore (2004)

 

MODEL-BASED AUDIO SOURCE SEPARATION [PDF]

Emmanuel Vincent, Maria G. Jafari, Samer A. Abdallah, Mark D. Plumbley and Mike E. Davies, Quenn Mary University of London (2006)

 

MODEL-BASED MONAURAL SOUND SEPARATION BY SPLIT-VQ OF SINUSOIDAL PARAMETERS [PDF]

P. Mowlaee Begzade Mahale and A. Sayadian, Department of Electrical Engineering , Amirkabir University of Technology, Tehran, Iran (2008)

 

MODEL-BASED MONAURAL SOURCE SEPARATION USING A VECTOR-QUANTIZED PHASE-VOCODER REPRESENTATION [PDF]

Daniel P. W. Ellis, Ron J. Weiss, LabROSA, Dept. of Elec. Eng., Columbia University, New York, New York (2006)

 

MODEL-BASED MULTIPLE PITCH TRACKING USING FACTORIAL HMMS: MODEL ADAPTATION AND INFERENCE [permalink]

Michael Wohlmayr and Franz Pernkopf, Member, IEEE, Signal Processing and Speech Communication Laboratory (SPSC), Graz University of Technology, Graz, Austria (2013)

 

MODEL-BASED STFT PHASE RECOVERY FOR AUDIO SOURCE SEPARATION [PDF]

Paul Magron, Roland Badeau, Senior Member, IEEE, and Bertrand David, Member, IEEE, LTCI, Télécom ParisTech, Université Paris-Saclay, Paris, France (2017)

MODEL-BASED TECHNIQUES FOR SIGNAL SEPARATION OF AUDIO SIGNALS (ADAPTIVE CONVERSION OF MONOPHONIC AUDIO TO TRUE MULTITRACK)

Dr John Szymanski, Senior Lecturer, Media Technology Research Group, Department of Electronics, University of York, Heslington, York, UK 

 

MODELING HIGH-DIMENSIONAL AUDIO SEQUENCES WITH RECURRENT NEURAL NETWORKS [PDF] 

Nicolas Boulanger-Lewandowski, Département d’informatique et de recherche opérationnelle, Faculté des arts et des sciences, Université de Montréal (2014)

 

MODELING PERCEPTUAL SIMILARITY OF AUDIO SIGNALS FOR BLIND SOURCE SEPARATION EVALUATION [PDF]

Brendan Fox, Andrew Sabin, Bryan Pardo, and Alec Zopf, Northwestern University, Evanston, Illinois (2007)

 

MODELING SPECTRAL SMOOTHNESS PRINCIPLE FOR MONAURAL VOICED SPEECH SEPARATION [permalink]

Wei Jiang, Wenju Liu, Pengfei Hu, National Laboratory of Pattern Recognition (NLPR), Institute of Automation Chinese Academy of Sciences, Beijing, China (2011)

 

MODELING THE SPECTRAL ENVELOPE OF MUSICAL INSTRUMENTS (slides) [PDF]

Juan José Burred, IRCAM, Équipe Analyse/Synthèse Axel Röbel / Xavier Rodet, Technical University of Berlin, Communication Systems Group, Prof. Thomas Sikora (2006)

 

MODELLING AND SEPARATION OF SINGING VOICE BREATHINESS IN POLYPHONIC MIXTURES [PDF]

Ricard Marxer, Jordi Janer, Music Technology Group, Universitat Pompeu Fabra, Barcelona, Spain, Proc. of the 16th Int. Conference on Digital Audio Effects (DAFx-13), Maynooth, Ireland (2013)

 

MODEL SELECTION FOR DEEP AUDIO SOURCE SEPARATION VIA CLUSTERING ANALYSIS [PDF]

Alisa Liu, Prem Seetharaman, Bryan Pardo, Northwestern University Computer Science Department Evanston, IL (2020)

MODIFIED REPET WITH SEGMENTATION FOR MUSIC/VOICE SEPARATION [PDF direct download]

Diana Mary David ECE dept, Marian Engineering college, Thiruvananthapuram, kerala, Sony S, Asst. Professor, ECE dept, Marian Engineering college, Thiruvananthapuram, kerala (2015)

 

MONAURAL AUDIO SEPARATION USING SPECTRAL TEMPLATE AND ISOLATED NOTE INFORMATION [permalink]

Anil Lal, Wenwu Wang, Department of Electronic Engineering, University of Surrey, United Kingdom (2012)

 

MONAURAL AUDIO SOURCE SEPARATION USING VARIATIONAL AUTOENCODERS [PDF]

Laxmi Pandey1, Anurendra Kumar1, Vinay Namboodiri1, 1Indian Institute of Technology Kanpur (2018)

 

MONAURAL AUDIO SOURCE SEPARATION USING VARIATIONAL AUTOENCODERS (presentation) (in Japanese)

Hiroshi Sekiguchi, Morikawa Lab (2019)

MONAURAL AUDIO SOURCE SEPARATION USING WAVE-U-NET & DEEP CONVOLUTIONAL NEURAL NETWORKS

Tanmay Bhagwat, University of Mumbai, Thane, Maharashtra (2019)

MONAURAL AUDIO SPEAKER SEPARATION USING SOURCE-CONTRASTIVE ESTIMATION [PDF]

Cory Stephenson, Patrick Callier, Abhinav Ganesh, and Karl Ni, Lab41, In-Q-Tel Laboratories, Menlo Park, California, USA (2017)

MONAURAL BLIND SOURCE SEPARATION IN THE CONTEXT OF VOCAL DETECTION [PDF]

Bernhard Lehner, Gerhard Widmer, Department of Computational Perception, Johannes Kepler University of Linz (2015)

 

MONAURAL MUSICAL SOUND SEPARATION [PDF]

Yipeng Li, M.S., The Ohio State University (2008)

 

MONAURAL MUSICAL SOUND SEPARATION BASED ON PITCH AND COMMON AMPLITUDE MODULATION [permalink]

Yipeng Li, John Woodruff, Student Member, IEEE, and DeLiang Wang, Fellow, IEEE (2009)

MONAURAL MUSICAL OCTAVE SOUND SEPARATION USING RELAXED EXTENDED COMMON AMPLITUDE MODULATION [permalink]

Yukai Gong and Longquan Dai (2021)

MONAURAL MUSIC SOURCE SEPARATION: NONNEGATIVITY, SPARSENESS, AND SHIFT-INVARIANCE [PDF]

Minje Kim, Seungjin Choi, Department of Computer Science, Pohang University of Science and Technology, Korea (2006)

 

MONAURAL MUSIC SOURCE SEPARATION USING A RESNET LATENT SEPARATOR NETWORK [PDF]

Gino Brunner, Nawel Naas, Sveinn Palsson, Oliver Richter, Roger Wattenhofer, Departement of Electrical Engineering and Information Technology, ETH Zurich, Zurich, Switzerland (2019)

MONAURAL MUSIC SOURCE SEPARATION USING CONVOLUTIONAL SPARSE CODING [PDF]

Ping-Keng Jao, Li Su, Member, IEEE Yi-Hsuan Yang, Member, IEEE, and Brendt Wohlberg, Senior Member, IEEE (2016)

MONAURAL MUSIC SEPARATION VIA SUPERVISED NON-NEGATIVE MATRIX FACTOR WITH SIDE-INFORMATION [PDF]

Ce Peng, M.A.Sc, Ottawa-Carleton Institute for Electrical and Computer Engineering, Department of Systems and Computer Engineering, Carleton University, Ottawa, Ontario, Canada (2017)

MONAURAL SCORE-INFORMED SOURCE SEPARATION FOR CLASSICAL MUSIC USING CONVOLUTIONAL NEURAL NETWORKS [PDF]

Marius Miron, Jordi Janer, Emilia Gómez, Music Technology Group, Universitat Pompeu Fabra, Barcelona (2017)

MONAURAL SEPARATION AND CLASSIFICATION OF NON-LINEAR TRANSFORMED INDEPENDENT SIGNALS: AN SVM PERSPECTIVE [PDF]

Sepp Hochreiter and Michael C. Mozer, Department of Computer Science, University of Colorado, Boulder, Colorado (2001)

 

MONAURAL SEPARATION OF INDEPENDENT ACOUSTICAL COMPONENTS [PDF]

Gert Cauwenberghs, Department of Electrical and Computer Engineering and Center for Language and Speech Processing, Johns Hopkins University, Baltimore, Maryland (1999)

 

MONAURAL SINGING VOICE AND ACCOMPANIMENT SEPARATION BASED ON GATED NESTED U-NET ARCHITECTURE [PDF direct download]

Haibo Geng 1,2 , Ying Hu 1,2, and Hao Huang 1,3, 1School of Information Science and Engineering, Xinjiang University, Urumqi, China, 2Key Laboratory of Signal Detection and Processing in Xinjiang Uygur Autonomous Region, Urumqi, China, Key Laboratory of Multilingual Information Technology in Xinjiang Uygur Autonomous Region, Urumqi, China (2020)

MONAURAL SINGING VOICE SEPARATION BY NON-NEGATIVE MATRIX PARTIAL CO-FACTORIZATION WITH TEMPORAL CONTINUITY AND SPARSITY CRITERIA [permalink]

Ying Hu, Liejun Wang, Hao Huang, Gang Zhou, The Institution of Information Science and Technology, Xinjiang University, Urumuqi, China (2016)

MONAURAL SINGING VOICE SEPARATION WITH SKIP-FILTERING CONNECTIONS AND RECURRENT INFERENCE OF TIME-FREQUENCY MASK [PDF]

Stylianos Ioannis Mimilakis∗, Konstantinos Drossos†, João F. Santos‡§, Gerald Schuller∗, Tuomas Virtanen†, Yoshua Bengio§,∗Fraunhofer IDMT, Ilmenau, Germany, †Tampere University of Technology, Tampere, Finland, §Université de Montréal, Montreal, Canada, ‡INRS-EMT, Montreal, Canada (2017)

MONAURAL SINGING VOICE SEPARATION WITH SKIP-FILTERING CONNECTIONS AND RECURRENT INFERENCE OF TIME-FREQUENCY MASK (demo)

Stylianos Ioannis Mimilakis∗, Konstantinos Drossos†, João F. Santos‡§, Gerald Schuller∗, Tuomas Virtanen†, Yoshua Bengio§,∗Fraunhofer IDMT, Ilmenau, Germany, †Tampere University of Technology, Tampere, Finland, §Université de Montréal, Montreal, Canada, ‡INRS-EMT, Montreal, Canada (2017)

MONAURAL SOUND SOURCE SEPARATION BY NONNEGATIVE MATRIX FACTORIZATION WITH TEMPORAL CONTINUITY AND SPARSENESS CRITERIA [PDF direct download]

Tuomas Virtanen, Digital Speech Processing in Noisy Environments (2007)

 

MONAURAL SOUND SOURCE SEPARATION BY PERCEPTUALLY WEIGHTED NON-NEGATIVE MATRIX FACTORIZATION [PDF]

Tuomas O. Virtanen, Tampere University of Technology, Institute of Signal Processing (2005)

 

MONAURAL SOUND SOURCE SEPARATION BY PERCEPTUALLY WEIGHTED NON-NEGATIVE MATRIX FACTORIZATION (demonstrations)
Tuomas O. Virtanen, Tampere University of Technology, Institute of Signal Processing (2005)

 

MONAURAL SOUND SOURCE SEPARATION USING COVARIANCE PROFILE OF PARTIALS [permalink]

Goel, P. ; Dept. of Electr. Eng., Indian Inst. of Sci., Bangalore, India ; Ramakrishnan, K.R. (2012)

MONAURAL SOURCE SEPARATION BASED ON ADAPTIVE DISCRIMINATIVE CRITERION IN NEURAL NETWORKS [permalink]

Yang Sun, Jonathon A. Chambers, Syed Mohsen Naqvi, School of Electrical and Electronics Engineering, Newcastle University, UK, Lei Zhu, Science College, Harbin Engineering University, P.R. China (2017) 

MONAURAL SOURCE SEPARATION BASED ON COMPLEX-VALUED DEEP NEURAL NETWORK (in Chinese) [permalink]

Shu-Fan Wang, Graduate Institute of Computer Science and Information Engineering, College of Electrical Engineering & Computer Science, National Central University, Taiwan (2016)

MONAURAL SOURCE SEPARATION FROM MUSICAL MIXTURES BASED ON TIME-FREQUENCY TIMBRE MODELS [PDF]

Juan José Burred, Thomas Sikora, Communication Systems Group, Technical University of Berlin, Germany (2007)

MONAURAL SOURCE SEPARATION IN THE WILD [PDF]

Tianjun Ma, Computer Science Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA (2020)

MONAURAL SOURCE SEPARATION USING A RANDOM FOREST CLASSIFIER [PDF]

Cosimo Riday, Saurabh Bhargava, Richard H.R. Hahnloser, and Shih-Chii Liu, Institute of Neuroinformatics, University of Zürich and ETH Zürich, Switzerland (2016)

MONAURAL SOURCE SEPARATION USING NEURAL NETWORKS [PDF]

Simon Kim, Mark Kwon, Sunmi Lee, Stanford University, Computer Science, Stanford, California, USA (2017)

MONAURAL SOURCE SEPARATION USING NONNEGATIVE MATRIX FACTORIZATION WITH GRAPH REGULARIZATION CONSTRAINT (in Chinese) [PDF]

Yan-Bo Lin, Tuan Pham, Yuan-Shan Lee, Jia-Ching Wang, Department of Computer Science and Information Engineering, National Central University, Taiwan (2015)

MONAURAL SOURCE SEPARATION USING RAMANUJAN SUBSPACE DICTIONARIES [permalink]

Hsueh-Wei Liao, Academia Sinica, Taipei, Taiwan, Li Su, Institute of Information Science, Academia Sinica, Taipei, Taiwan (2018)

MONAURAL SOURCE SEPARATION USING SPECTRAL CUES [PDF]

Barak A. Pearlmutter - Hamilton Institute, National University of Ireland Maynooth, Co. Kildare, Ireland, Anthony M. Zador - Cold Spring Harbor Laboratory, Cold Spring Harbor, New York (2004)

 

MONAURAL SPEECH/MUSIC SOURCE SEPARATION USING DISCRETE ENERGY SEPARATION ALGORITHM [permalink]

Yevgeni Litvin a, Israel Cohen a, Dan Chazan b, a Department of Electrical Engineering, Technion - Israel Institute of Technology, Technion City, Haifa 32000, Israel, b IBM Research Laboratory in Haifa, Israel (2010)

 

MONAURAL SPEECH SEPARATION [PDF]

Guoning Hu - Biophysics Program, The Ohio State University, Columbus, Ohio, DeLiang Wang - Department of Computer and Information Science & Center of Cognitive Science, The Ohio State University, Columbus, Ohio (2003)

 

MONAURAL SPEECH SEPARATION BASED ON COMPUTATIONAL AUDITORY SCENE ANALYSIS AND OBJECTIVE QUALITY ASSESSMENT OF SPEECH [permalink]

Peng Li, Bo Xu, High-Tech Innovation Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China, Yong Guan, Wenju Liu, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China (2006)

 

MONAURAL SPEECH SEPARATION BASED ON MULTI-SCALE FAN-CHIRP TRANSFORM [permalink]

Pei Zhao, Zhiping Zhang, Xihong Wu, Speech and Hearing Research Center, State Key Laboratory of Machine Perception, Peking University, Beijing, China (2008)

 

MONAURAL SPEECH SEPARATION BY SUPPORT VECTOR MACHINES: BRIDGING THE DIVIDE BETWEEN SUPERVISED AND UNSUPERVISED LEARNING METHODS [permalink]

Sepp Hochreiter1 and Michael C. Mozer2, 1 Institute of Bioinformatics, Johannes Kepler University, Linz, Austria, 2 Department of Computer Science, University of Colorado, Boulder, Colorado (2007)

 

MONAURAL SPEECH SEPARATION USING SOURCE-ADAPTED MODELS [permalink]

Ron J. Weiss and Daniel P. W. Ellis, LabROSA, Dept. of Electrical Engineering, Columbia University (2007)

 

MONAURAL SPEECH SEPARATION THROUGH HARMONIC-TEMPORAL CLUSTERING OF THE POWER SPECTRUM [PDF direct download]

Jonathan Le Roux, Hirokazu Kameoka, Nobutaka Ono (The University of Tokyo), Alain de Cheveigné (CNRS, ENS, Paris 5) and Shigeki Sagayama (The University of Tokyo) (2007)

 

MONAURAL SPEECH SOURCE SEPARATION BY ESTIMATING THE POWER SPECTRUM USING MULTI-FREQUENCY HARMONIC PRODUCT SPECTRUM [permalink]

Ayllon, David; Gil-Pita, Roberto; Rosa-Zurera, Manuel, University of Alcala, Alcalá de Henares, Spain (2013)

MONOAURAL AUDIO SOURCE SEPARATION USING DEEP CONVOLUTIONAL NEURAL NETWORKS [PDF direct download]

Pritish Chandna, Marius Miron, Jordi Janer, and Emilia Gómez,Music Technology Group, Universitat Pompeu Fabra, Barcelona (2017)

MONOPHONIC CONSTRAINED NON-NEGATIVE SPARSE CODING USING INSTRUMENT MODELS FOR AUDIO SEPARATION AND TRANSCRIPTION OF MONOPHONIC SOURCE-BASED POLYPHONIC MIXTURES [permalink]

Francisco José Rodríguez-Serrano, Julio José Carabias-Orti, Pedro Vera-Candeas, Francisco Jesús Canadas-Quesada, Nicolás Ruiz-Reyes, Telecommunication Engineering Department, University of Jaen, Jaen, Spain (2013)

 

MONOPHONIC INSTRUMENT SOUND SEGREGATION BY CLUSTERING NMF COMPONENTS BASED ON BASIS SIMILARITY AND GAIN DISJOINTNESS [PDF]

Kazuma Murao, Masahiro Nakano, Yu Kitano, Nobutaka Ono, Shigeki Sagayama, Graduate School of Information Science and Technology, The University of Tokyo, Japan (2010)

 

MONOPHONIC SINGING VOICE SEPARATION BASED ON DEEP LEARNING [permalink]

Yutian Wang, Zhao Zhang, Zheng Wang, JuanJuan Cai, Hui Wang (2019)

MONOPHONIC SOUND SOURCE SEPARATION BY NON-NEGATIVE SPARSE AUTOENCODERS [permalink]

Keiki Zen, Masahiro Suzuki, Haruhiko Sato, Satoshi Oyama, Masahito Kurihara, Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Hokkaido, Japan (2014)

 

MONOPHONIC SOUND SOURCE SEPARATION WITH AN UNSUPERVISED NETWORK OF SPIKING NEURONES [permalink]

Ramin Pichevar, Jean Rouat, Département de génie électrique et génie informatique, Université de Sherbrooke, Sherbrooke, Québec, Canada (2007)

MONO-TO-STEREO & BEYOND AUDIO SIGNAL SEPARATION (chapter 7, pages 105-134) [PDF]

Mohd Ibrahim bin Shapiai, Penerbit Universiti Teknologi Malaysia (2008)

 

MONO-TO-STEREO BLIND UPMIX USING NON-NEGATIVE MATRIX FACTORIZATION AND DECORRELATOR (in Korean) [PDF]

Keunwoo Choi, Sang Bae Chon, Seokjin Lee, and Koeng-Mo Sung, Journal of Acoustic Society of Korea (2010)

MONO-TO-STEREO UPMIXING [permalink]

Christian Uhle and Patrick Gampp, Fraunhofer Institute for Integrated Circuits, Erlangen, Germany (2016)

MOTION INFORMED AUDIO SOURCE SEPARATION [PDF]

Sanjeel Parekh⋆†, Slim Essie⋆, Alexey Ozerov†, Ngoc Q. K. Duong†, Patrick Pérez†, Gaël Richard⋆,⋆ LTCI, Télécom ParisTech, Université Paris–Saclay, Paris, France, † Technicolor, Cesson Sévigné, France (2017)

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