PROBABILISTIC LATENT TENSOR FACTORIZATION FRAMEWORK FOR AUDIO MODELING

被引：0

作者：

Cemgil, Ali Taylan ^{[1
,2
]}

Simsekli, Umut ^{[1
]}

Subakan, Yusuf Cem ^{[2
]}

机构：

[1] Bogazici Univ, Dept Comp Engn, TR-34342 Istanbul, Turkey

[2] Bogazici Univ, Dept Elect & Elect Engn, TR-34342 Istanbul, Turkey

来源：

2011 IEEE WORKSHOP ON APPLICATIONS OF SIGNAL PROCESSING TO AUDIO AND ACOUSTICS (WASPAA) | 2011年

关键词：

Audio Modeling; Probabilistic Latent Tensor Factorization; Factor graphs; Statistical Inference; Message Passing; NONNEGATIVE MATRIX FACTORIZATION;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

This paper introduces probabilistic latent tensor factorization (PLTF) as a general framework for hierarchical modeling of audio. This framework combines practical aspects of graphical modeling of machine learning with tensor factorization models. Once a model is constructed in the PLTF framework, the estimation algorithm is immediately available. We illustrate our approach using several popular models such as NMF or NMF2D and provide extensions with simulation results on real data for key audio processing tasks such as restoration and source separation.

引用

页码：137 / 140

页数：4

共 50 条

[21] Tensor Networks for Probabilistic Sequence Modeling
Miller, Jacob
Rabusseau, Guillaume
Terilla, John
[J]. 24TH INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS (AISTATS), 2021, 130
[22] Characterizing Flight Delay Profiles with a Tensor Factorization Framework
Zhang, Mingyuan
Chen, Shenwen
Sun, Lijun
Du, Wenbo
Cao, Xianbin
[J]. ENGINEERING, 2021, 7 (04) : 465 - 472
[23] INFINITE PROBABILISTIC LATENT COMPONENT ANALYSIS FOR AUDIO SOURCE SEPARATION
Yoshii, Kazuyoshi
Nakamura, Eita
Itoyama, Katsutoshi
Goto, Masataka
[J]. 2017 IEEE 27TH INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING, 2017,
[24] COLLABORATIVE AUDIO ENHANCEMENT USING PROBABILISTIC LATENT COMPONENT SHARING
Kim, Minje
Smaragdis, Paris
[J]. 2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2013, : 896 - 900
[25] The Cumulant Tensor Framework for the Probabilistic Power Flow
Vykhodtsev, Anton V.
Rosehart, William D.
Zareipour, Hamidreza
[J]. 2020 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM), 2020,
[26] Incremental Multi-Domain Learning with Network Latent Tensor Factorization
Bulat, Adrian
Kossaifi, Jean
Tzimiropoulos, Georgios
Pantic, Maja
[J]. THIRTY-FOURTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THE THIRTY-SECOND INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE AND THE TENTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2020, 34 : 10470 - 10477
[27] STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization
Kargas, Nikos
Qian, Cheng
Sidiropoulos, Nicholas D.
Xiao, Cao
Glass, Lucas M.
Sun, Jimeng
[J]. THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2021, 35 : 4830 - 4837
[28] A Probabilistic Tensor Factorization Approach to Detect Anomalies in Spatiotemporal Traffic Activities
Wang, Xudong
Fagette, Antoine
Sartelet, Pascal
Sun, Lijun
[J]. 2019 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC), 2019, : 1658 - 1663
[29] MULTICHANNEL AUDIO UPMIXING BASED ON NON-NEGATIVE TENSOR FACTORIZATION REPRESENTATION
Nikunen, J.
Virtanen, T.
Vilermo, M.
[J]. 2011 IEEE WORKSHOP ON APPLICATIONS OF SIGNAL PROCESSING TO AUDIO AND ACOUSTICS (WASPAA), 2011, : 33 - 36
[30] Blind Separation of Audio Mixtures Through Nonnegative Tensor Factorization of Modulation Spectrograms
Barker, Tom
Virtanen, Tuomas
[J]. IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2016, 24 (12) : 2377 - 2389

← 1 2 3 4 5 →