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Harmonic-Temporal Factor Decomposition for Unsupervised Monaural Separation of Harmonic Sounds

Tomohiko Nakamura, Hirokazu Kameoka
2020 IEEE/ACM Transactions on Audio Speech and Language Processing  
We address the problem of separating a monaural mixture of harmonic sounds into the audio signals of individual semitones in an unsupervised manner.  ...  Hence, we propose a monaural audio source separation framework, harmonic-temporal factor decomposition (HTFD), by developing a spectrogram model that encompasses the features of the models used in the  ...  ACKNOWLEDGMENT The authors would like to thank Kotaro Shikata and Norihiro Takamune for their fruitful discussions.  ... 
doi:10.1109/taslp.2020.3037487 fatcat:4auwrbeuvfcxfpv3zeliq74d3a

Percussive/harmonic sound separation by non-negative matrix factorization with smoothness/sparseness constraints

Francisco Jesus Canadas-Quesada, Pedro Vera-Candeas, Nicolas Ruiz-Reyes, Julio Carabias-Orti, Pablo Cabanas-Molero
2014 EURASIP Journal on Audio, Speech, and Music Processing  
In this paper, unsupervised learning is used to separate percussive and harmonic sounds from monaural non-vocal polyphonic signals.  ...  and harmonic sounds is integrated into the decomposition process.  ...  Conclusions This paper presents an unsupervised learning process for separating percussive and harmonic sounds from monaural instrumental music.  ... 
doi:10.1186/s13636-014-0026-5 fatcat:hdodcvmgp5bftd5gsgzs2zixm4

Online Harmonic/Percussive Separation Using Smoothness/Sparseness Constraints

F. Canadas-Quesada, P. Vera-Candeas, N. Ruiz-Reyes, P. Alonso, J. Ranilla
2015 Proceedings of the SMC Conferences  
Acknowledgments This work was supported by the Andalusian Business, Science and Innovation Council under project P2010-TIC-6762 (FEDER) and the Spanish Ministry of Economy and Competitiveness under Projects  ...  To overcome this problem, we proposed [9] an unsupervised system that can separate percussive and harmonic sounds in monaural music integrating percussive and harmonic sound features into the NMF decomposition  ...  Each separated spectrogram exhibits specific spectro-temporal features for percussive or harmonic sounds.  ... 
doi:10.5281/zenodo.851017 fatcat:4uhha744pnee5erhxix6pdvd4y

Blind rhythmic source separation: Nonnegativity and repeatability

Minje Kim, Jiho Yoo, Kyeongok Kang, Seungjin Choi
2010 2010 IEEE International Conference on Acoustics, Speech and Signal Processing  
Moreover, temporal repeatability of the rhythmic sound sources is implicated as common rhythmic property among segments of an input mixture signal.  ...  An extension of nonnegative matrix factorization (NMF) is used to analyze multiple relationships between spectral and temporal properties in the given input matrices.  ...  Although NMF has been used as an effective tool for separating musical sources from their monaural mixture, the parts-based representation does not always guarantee satisfying separation for various kinds  ... 
doi:10.1109/icassp.2010.5495205 dblp:conf/icassp/KimYKC10 fatcat:gdzvlosw4na4xpg6hj2nwvxwna

Monophonic Instrument Sound Segregation By Clustering Nmf Components Based On Basis Similarity And Gain Disjointness

Kazuma Murao, Masahiro Nakano, Yu Kitano, Nobutaka Ono, Shigeki Sagayama
2010 Zenodo  
This research was supported by CrestMuse Project under JST and Grant-in-Aid for Scientific Research (KAKENHI) (A) 20240017.  ...  This paper discusses a method to separate monaural musical audio into individual musical instruments. Sound source separation for music signal has been widely investigated recently.  ...  Because any prior information for instrumental sound sources cannot be used, some unsupervised methods make assumption about common harmonic structure [4, 5] or employ the excitationfilter model of sound  ... 
doi:10.5281/zenodo.1417112 fatcat:uu2woe6hyzcrfgtjfu23jvoxnu

2020 Index IEEE/ACM Transactions on Audio, Speech, and Language Processing Vol. 28

2020 IEEE/ACM Transactions on Audio Speech and Language Processing  
., +, TASLP 2020 901-913 Simultaneous Tracking and Separation of Multiple Sources Using Factor Graph Model.  ...  ., +, TASLP 2020 1729-1744 A Deep Learning Framework for Robust DOA Estimation Using Spherical Harmonic Decomposition.  ...  T Target tracking Multi-Hypothesis Square-Root Cubature Kalman Particle Filter for Speaker Tracking in Noisy and Reverberant Environments. Zhang, Q., +, TASLP 2020 1183 -1197  ... 
doi:10.1109/taslp.2021.3055391 fatcat:7vmstynfqvaprgz6qy3ekinkt4

Fast bayesian nmf algorithms enforcing harmonicity and temporal continuity in polyphonic music transcription

Nancy Bertin, Roland Badeau, Emmanuel Vincent
2009 2009 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics  
This article presents theoretical and experimental results about constrained non-negative matrix factorization (NMF) in a Bayesian framework, enforcing both spectral harmonicity and temporal continuity  ...  We exhibit fast multiplicative update rules to perform the decomposition, which are then applied to perform polyphonic piano music transcription.  ...  NMF has been widely and successfully used to process audio signals, including various tasks such as monaural sound source separation [1] and music transcription [2] .  ... 
doi:10.1109/aspaa.2009.5346531 dblp:conf/waspaa/BertinBV09 fatcat:t3mjjxr4ezg3rapxz2m5qyelym

Towards Solving the Bottleneck of Pitch-based Singing Voice Separation

Bilei Zhu, Wei Li, Linwei Li
2015 Proceedings of the 23rd ACM international conference on Multimedia - MM '15  
A majority of existing algorithms are based on singing pitch detection, and take the detected pitch as the cue to identify and separate the harmonic structure of the singing voice.  ...  Singing voice separation from accompaniment in monaural music recordings is a crucial technique in music information retrieval.  ...  Specifically, the algorithm first has a rough estimation for the pitch of the singing voice and then applies it to separate the singing voice by considering harmonicity and temporal continuity.  ... 
doi:10.1145/2733373.2806257 dblp:conf/mm/Zhu0L15 fatcat:rt2ti3tatjbtngsosmwohaw7by

Monaural Sound Source Separation by Nonnegative Matrix Factorization With Temporal Continuity and Sparseness Criteria

Tuomas Virtanen
2007 IEEE Transactions on Audio, Speech, and Language Processing  
An unsupervised learning algorithm for the separation of sound sources in one-channel music signals is presented.  ...  Index Terms-Acoustic signal analysis, audio source separation, blind source separation, music, nonnegative matrix factorization, sparse coding, unsupervised learning.  ...  UNSUPERVISED LEARNING ALGORITHMS IN SOUND SOURCE SEPARATION Most of the above-mentioned algorithms for unsupervised sound source separation are based on a signal model where the magnitude or power spectrum  ... 
doi:10.1109/tasl.2006.885253 fatcat:vtahqd4wxrfdvipq7bx5zd5sti

Table of Contents

2021 IEEE/ACM Transactions on Audio Speech and Language Processing  
Prawda Harmonic-Temporal Factor Decomposition for Unsupervised Monaural Separation of Harmonic Sounds . . . . . . . . ......Kameoka CTC-Based Learning of Chroma Features for Score-Audio Music Retrieval  ...  for DOA Estimation and Acoustic Source Separation . . . . . . . . . . . . . ....Hacıhabiboglu Evolving Multi-Resolution Pooling CNN for Monaural Singing Voice Separation . . . . . . . . . . . . . . .  ...  Speech Enhancement and Separation  ... 
doi:10.1109/taslp.2021.3137066 fatcat:ocit27xwlbagtjdyc652yws4xa

Table of Contents

2020 IEEE/ACM Transactions on Audio Speech and Language Processing  
Yin 2095 Causal Deep CASA for Monaural Talker-Independent Speaker Separation . . . . . . . . . . . . . . . . . . . . . .Y. Liu and D. L.  ...  Hermansky 646 Spherical-Harmonic-Domain Feedforward Active Noise Control Using Sparse Decomposition of Reference Signals from Distributed Sensor Arrays . . . . . . . . . . . . Y. Maeno, Y.  ... 
doi:10.1109/taslp.2020.3046148 fatcat:hirdphjf6zeqdjzwnwlwlamtb4

Enforcing Harmonicity and Smoothness in Bayesian Non-Negative Matrix Factorization Applied to Polyphonic Music Transcription

Nancy Bertin, Roland Badeau, Emmanuel Vincent
2010 IEEE Transactions on Audio, Speech, and Language Processing  
Index Terms-Non-negative matrix factorization (NMF), music transcription, audio source separation, unsupervised machine learning, Bayesian regression.  ...  A model of superimposed Gaussian components including harmonicity is proposed, while temporal continuity is enforced through an inverse-Gamma Markov chain prior.  ...  The authors would like to thank Cédric Févotte for his decisive influence on the Bayesian orientation of this work, wise advice on literature review, and support.  ... 
doi:10.1109/tasl.2010.2041381 fatcat:liigkjdqmrclpkdqw56oqsb2u4

Enforcing Harmonicity and Smoothness in Bayesian Non-negative Matrix Factorization Applied to Polyphonic Music Transcription

N. Bertin, R. Badeau, E. Vincent
2009 IEEE Transactions on Audio, Speech, and Language Processing  
Index Terms-Non-negative matrix factorization (NMF), music transcription, audio source separation, unsupervised machine learning, Bayesian regression.  ...  A model of superimposed Gaussian components including harmonicity is proposed, while temporal continuity is enforced through an inverse-Gamma Markov chain prior.  ...  The authors would like to thank Cédric Févotte for his decisive influence on the Bayesian orientation of this work, wise advice on literature review, and support.  ... 
doi:10.1109/tasl.2009.2035199 fatcat:mfmhhgtz3zbtbouegodkh6vdki

Segregating Complex Sound Sources through Temporal Coherence

Lakshmi Krishnan, Mounya Elhilali, Shihab Shamma, Michael Lewicki
2014 PLoS Computational Biology  
A new approach for the segregation of monaural sound mixtures is presented based on the principle of temporal coherence and using auditory cortical representations.  ...  Temporal coherence is the notion that perceived sources emit coherently modulated features that evoke highly-coincident neural response patterns.  ...  Asif Ghazanfar for providing the inter-lip distance data. Author Contributions Conceived and designed the experiments: LK SS ME. Performed the experiments: LK. Analyzed the data: LK SS.  ... 
doi:10.1371/journal.pcbi.1003985 pmid:25521593 pmcid:PMC4270434 fatcat:vn6zwpnd6jfape6m5m3kaenf3e

A Novel Singing Voice Separation Method Based on Sparse Non-Negative Matrix Factorization and Low-Rank Modeling

S. Mavaddati
2019 Iranian Journal of Electrical and Electronic Engineering  
This separation procedure is done using a decomposition model based on the spectrogram of singing voice signals.  ...  The average improvement values of the proposed separation algorithm for PESQ, fwSegSNR, SDI, and GNSDR measures in comparison with previous separation methods in two defined test scenario and three mentioned  ...  In [11] , a recurrent neural network-based decomposition algorithm is proposed to capture long-term temporal dependencies between data structures using NMF and model sound mixtures.  ... 
doaj:7bb13e894aa5463faf1af08330d208c5 fatcat:tt7survcijexbmt6kygg3cxqlu
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