MULTICHANNEL HR-NMF FOR MODELLING CONVOLUTIVE MIXTURES OF NON-STATIONARY SIGNALS IN THE TIME-FREQUENCY DOMAIN

被引：0

作者：

Badeau, Roland ^{[1
]}

Plumbley, Mark D. ^{[2
]}

机构：

[1] Telecom ParisTech, Inst Mines Telecom, CNRS LTCI, Paris, France

[2] Queen Mary Univ London, Ctr Digital Mus, Sch Elect Engn & Comp Sci, London, England

来源：

2013 IEEE WORKSHOP ON APPLICATIONS OF SIGNAL PROCESSING TO AUDIO AND ACOUSTICS (WASPAA) | 2013年

关键词：

Non-stationary signal modelling; Time-frequency analysis; Separation of convolutive mixtures; Multichannel signal analysis; Variational EM algorithm; NONNEGATIVE MATRIX FACTORIZATION; SEPARATION;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

Several probabilistic models involving latent components have been proposed for modelling time-frequency (TF) representations of audio signals (such as spectrograms), notably in the nonnegative matrix factorization (NMF) literature. Among them, the recent high resolution NMF (HR-NMF) model is able to take both phases and local correlations in each frequency band into account, and its potential has been illustrated in applications such as source separation and audio inpainting. In this paper, HR-NMF is extended to multichannel signals and to convolutive mixtures. A fast variational expectation-maximization (EM) algorithm is proposed to estimate the enhanced model. This algorithm is applied to a stereophonic piano signal, and proves capable of accurately modelling reverberation and restoring missing observations.

引用

页数：4

共 50 条

[21] Blind Separation of Convolutive Mixtures of Non-stationary Sources Using Joint Block Diagonalization in the Frequency Domain
Saylani, Hicham
Hosseini, Shahram
Deville, Yannick
[J]. LATENT VARIABLE ANALYSIS AND SIGNAL SEPARATION, 2010, 6365 : 97 - +
[22] Time-frequency analysis of nonlinear and non-stationary weak signals of corona discharge
Wang, Lei
Liu, Shanghe
Wei, Ming
Hu, XiaoFeng
[J]. 7TH INTERNATIONAL CONFERENCE ON APPLIED ELECTROSTATICS (ICAES-2012), 2013, 418
[23] Refined linear chirplet transform for time-frequency analysis of non-stationary signals
Zhang, Jingyao
Bao, Yuanfeng
Aoki, Takayoshi
Yamashita, Takuzo
[J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2025, 223
[24] PROBABILISTIC TIME-FREQUENCY SOURCE-FILTER DECOMPOSITION OF NON-STATIONARY SIGNALS
Badeau, Roland
Plumbley, Mark D.
[J]. 2013 PROCEEDINGS OF THE 21ST EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), 2013,
[25] Reconstruction of Non-stationary Signals with Missing Samples Using Time-frequency Filtering
Khan, Nabeel Ali
Mohammadi, Mokhtar
[J]. CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2018, 37 (08) : 3175 - 3190
[26] Blind Separation of Non-stationary Convoluted Mixtures Based on Time-frequency Analysis
Wang, Peng
Cao, Jihua
Ni, Xiaochang
[J]. MATERIALS PROCESSING TECHNOLOGY II, PTS 1-4, 2012, 538-541 : 2571 - 2575
[27] A methodology for time-frequency image processing applied to the classification of non-stationary multichannel signals using instantaneous frequency descriptors with application to newborn EEG signals
Boualem Boashash
Larbi Boubchir
Ghasem Azemi
[J]. EURASIP Journal on Advances in Signal Processing, 2012
[28] A methodology for time-frequency image processing applied to the classification of non-stationary multichannel signals using instantaneous frequency descriptors with application to newborn EEG signals
Boashash, Boualem
Boubchir, Larbi
Azemi, Ghasem
[J]. EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2012,
[29] CLASSIFICATION IN THE GABOR TIME-FREQUENCY DOMAIN OF NON-STATIONARY SIGNALS EMBEDDED IN HEAVY NOISE WITH UNKNOWN STATISTICAL DISTRIBUTION
Swiercz, Ewa
[J]. INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE, 2010, 20 (01) : 135 - 147
[30] A High-Efficiency Optimized Detection Algorithm for Non-Stationary Marine Acoustic Signals in the Time-Frequency Domain
Cao, Tianyu
Bian, Mengqi
Yang, Yichen
Xu, Zhongwei
Zhao, Xiaoqun
[J]. IEEE ACCESS, 2022, 10 : 64085 - 64094

← 1 2 3 4 5 →