An overview of informed audio source separation

Autor: Laurent Daudet, Gael Richard, Antoine Liutkus, Jean-Louis Durrieu

Publikováno v: WIAMIS 2013-The 14th International Workshop on Image and Audio Analysis for Multimedia Interactive Services
WIAMIS 2013-The 14th International Workshop on Image and Audio Analysis for Multimedia Interactive Services, Jul 2013, Paris, France. pp.1-4, ⟨10.1109/WIAMIS.2013.6616139⟩
WIAMIS

International audience; Audio source separation consists in recovering different unknown signals called sources by filtering their observed mixtures. In music processing, most mixtures are stereophonic songs and the sources are the individual signals

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e447a0717fb490af093d27788d692a33
https://hal.archives-ouvertes.fr/hal-00958661/file/WIAMIS.pdf

Combining monaural source separation with Long Short-Term Memory for increased robustness in vocalist gender recognition

Autor: Florian Eyben, Felix Weninger, Gael Richard, Jean-Louis Durrieu, Björn Schuller

Publikováno v: ICASSP 2011-2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
ICASSP 2011-2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2011, Prague, France. pp.2196-2199, ⟨10.1109/ICASSP.2011.5946764⟩
ICASSP

We present a novel and unique combination of algorithms to detect the gender of the leading vocalist in recorded popular music. Building on our previous successful approach that enhanced the harmonic parts by means of Non-Negative Matrix Factorizatio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4175f82d5fcb8aa3e63cbb72057e0a3e
https://hal.inria.fr/hal-02714095

Source/Filter Model for Unsupervised Main Melody Extraction From Polyphonic Audio Signals

Autor: Cédric Févotte, Gael Richard, Jean-Louis Durrieu, Bertrand David

Publikováno v: IEEE Transactions on Audio, Speech and Language Processing
IEEE Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2010

International audience; Extracting the main melody from a polyphonic music recording seems natural even to untrained human listeners. To a certain extent it is related to the concept of source separation, with the human ability of focusing on a speci

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3f36229b78e974f80c099f0cab211ea4
https://hal.archives-ouvertes.fr/hal-02652995/file/TSALP_Durrieu10.pdf

Nonnegative matrix factorization with the Itakura-Saito divergence: with application to music analysis

Autor: Nancy Bertin, Jean-Louis Durrieu, Cédric Févotte

Publikováno v: Neural computation. 21(3)

This letter presents theoretical, algorithmic, and experimental results about nonnegative matrix factorization (NMF) with the Itakura-Saito (IS) divergence. We describe how IS-NMF is underlaid by a well-defined statistical model of superimposed gauss

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5bae94fdfba4735ce429069944b6c52c
https://pubmed.ncbi.nlm.nih.gov/18785855

Single sensor singer/music separation using a source/filter model of the singer voice

Autor: Bertrand David, Gael Richard, Jean-Louis Durrieu

Publikováno v: The Journal of the Acoustical Society of America. 123:3800-3800

Separating the singer voice from polyphonic music signals has many useful applications, such as demixing/remixing, desoloing or audio indexing. In the works of Benaroya on single sensor blind source separation, the signals are modeled by Gaussian mix

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1cd4a778e41bf8a75e1d1aaa3742a347
https://doi.org/10.1121/1.2935487