2nd Call for Papers: Special Issue on Informed Acoustic Source Separation; EURASIP Journal on Advances in Signal Processing (Ozerov Alexey )


Subject: 2nd Call for Papers: Special Issue on Informed Acoustic Source Separation; EURASIP Journal on Advances in Signal  Processing
From:    Ozerov Alexey  <Alexey.Ozerov@xxxxxxxx>
Date:    Mon, 11 Feb 2013 09:59:11 +0100
List-Archive:<http://lists.mcgill.ca/scripts/wa.exe?LIST=AUDITORY>

--_000_B02BDB2D74045345919286EDF0DA730A0854A8CC1BMOPESMBX01eut_ Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable We apologize for cross-distribution and multiple copies. *************************************************** 2nd CALL FOR PAPERS EURASIP Journal on Advances in Signal Processing Special Issue on Informed Acoustic Source Separation The complete call of papers is accessible at: http://asp.eurasipjournals.com/sites/10233/pdf/H9386_DF_CFP_EURASIP_JASP_A4= _3.pdf DEADLINE: PAPER SUBMISSION: 31st May 2013 ---------------------------------------------------------------------------= --------------------------- Short Description The proposed topic of this special issue is informed acoustic source separa= tion. As source separation has long become a field of interest in the signa= l processing community, recent works increasingly point out the fact that s= eparation can only be reliably achieved in real-world use cases when accura= te prior information can be successfully incorporated. Informed separation = algorithms can be characterized by the fact that case-specific prior knowle= dge is made available to the algorithm for processing. In this respect, the= y contrast with blind methods for which no specific prior information is av= ailable. Following on the success of the special session on the same topic in EUSIPC= O 2012 at Bucharest, we would like to present recent methods, discuss the t= rends and perspectives of this domain and to draw the attention of the sign= al processing community to this important problem and its potential applica= tions. We are interested in both methodological advances and applications. = Topics of interest include (but are not limited to): * Sparse decomposition methods * Subspace learning methods for sparse decomposition * Non-negative matrix / tensor factorization * Robust principal component analysis * Probabilistic latent component analysis * Independent component analysis * Multidimensional component analysis * Multimodal source separation * Video-assisted source separation * Spatial audio object coding * Reverberant models for source separation * Score-informed source separation * Language-informed speech separation * User-guided source separation * Source separation informed by cover version * Informed source separation applied to speech, music or environmental sign= als * ... ------------------- Guest Editors Taylan Cemgil, Bogazici University, Turkey, Tuomas Virtanen, Tampere University of Technology, Finland, Alexey Ozerov, Technicolor, France, Derry Fitzgerald, Dublin institute of Technology, Ireland, Lead Guest Editor: Ga=EBl Richard, Institut Mines-T=E9l=E9com, T=E9l=E9com ParisTech, CNRS-LTC= I, France. --_000_B02BDB2D74045345919286EDF0DA730A0854A8CC1BMOPESMBX01eut_ Content-Type: text/html; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable <html xmlns:v=3D"urn:schemas-microsoft-com:vml" xmlns:o=3D"urn:schemas-micr= osoft-com:office:office" xmlns:w=3D"urn:schemas-microsoft-com:office:word" = xmlns:m=3D"http://schemas.microsoft.com/office/2004/12/omml" xmlns=3D"http:= //www.w3.org/TR/REC-html40"><head><meta http-equiv=3DContent-Type content= =3D"text/html; charset=3Diso-8859-1"><meta name=3DGenerator content=3D"Micr= osoft Word 12 (filtered medium)"><style><!-- /* Font Definitions */ @xxxxxxxx {font-family:"MS Mincho"; panose-1:2 2 6 9 4 2 5 8 3 4;} @xxxxxxxx {font-family:"Cambria Math"; panose-1:2 4 5 3 5 4 6 3 2 4;} @xxxxxxxx {font-family:Calibri; panose-1:2 15 5 2 2 2 4 3 2 4;} @xxxxxxxx {font-family:"\@xxxxxxxx Mincho"; panose-1:2 2 6 9 4 2 5 8 3 4;} /* Style Definitions */ p.MsoNormal, li.MsoNormal, div.MsoNormal {margin:0cm; margin-bottom:.0001pt; font-size:11.0pt; font-family:"Calibri","sans-serif";} a:link, span.MsoHyperlink {mso-style-priority:99; color:blue; text-decoration:underline;} a:visited, span.MsoHyperlinkFollowed {mso-style-priority:99; color:purple; text-decoration:underline;} span.EmailStyle17 {mso-style-type:personal-compose; font-family:"Calibri","sans-serif"; color:windowtext;} .MsoChpDefault {mso-style-type:export-only;} @xxxxxxxx WordSection1 {size:612.0pt 792.0pt; margin:72.0pt 72.0pt 72.0pt 72.0pt;} div.WordSection1 {page:WordSection1;} --></style><!--[if gte mso 9]><xml> <o:shapedefaults v:ext=3D"edit" spidmax=3D"1026" /> </xml><![endif]--><!--[if gte mso 9]><xml> <o:shapelayout v:ext=3D"edit"> <o:idmap v:ext=3D"edit" data=3D"1" /> </o:shapelayout></xml><![endif]--></head><body lang=3DEN-US link=3Dblue vli= nk=3Dpurple><div class=3DWordSection1><p class=3DMsoNormal style=3D'mso-mar= gin-top-alt:auto;mso-margin-bottom-alt:auto'>We apologize for cross-distrib= ution and multiple copies. <br><br>****************************************= *********** <br><br>2nd CALL FOR PAPERS <br><br>EURASIP Journal on Advances= in Signal Processing <br>Special Issue on Informed Acoustic Source Separat= ion <br><br>The complete call of papers is accessible at: <br><a href=3D"ht= tp://asp.eurasipjournals.com/sites/10233/pdf/H9386_DF_CFP_EURASIP_JASP_A4_3= .pdf">http://asp.eurasipjournals.com/sites/10233/pdf/H9386_DF_CFP_EURASIP_J= ASP_A4_3.pdf</a> <br><br>DEADLINE: PAPER SUBMISSION: 31st May 2013 <br><br>= ---------------------------------------------------------------------------= --------------------------- <br>Short Description <br><br>The proposed topi= c of this special issue is informed acoustic source separation. As source s= eparation has long become a field of interest in the signal processing comm= unity, recent works increasingly point out the fact that separation can onl= y be reliably achieved in real-world use cases when accurate prior informat= ion can be successfully incorporated. Informed separation algorithms can be= characterized by the fact that case-specific prior knowledge is made avail= able to the algorithm for processing. In this respect, they contrast with b= lind methods for which no specific prior information is available. <br>Foll= owing on the success of the special session on the same topic in EUSIPCO 20= 12 at Bucharest, we would like to present recent methods, discuss the trend= s and perspectives of this domain and to draw the attention of the signal p= rocessing community to this important problem and its potential application= s. We are interested in both methodological advances and applications. Topi= cs of interest include (but are not limited to): <br><br>&#8226; Sparse dec= omposition methods <br>&#8226; Subspace learning methods for sparse decompo= sition <br>&#8226; Non-negative matrix / tensor factorization <br>&#8226; R= obust principal component analysis <br>&#8226; Probabilistic latent compone= nt analysis <br>&#8226; Independent component analysis <br>&#8226; Multidim= ensional component analysis <br>&#8226; Multimodal source separation <br>&#= 8226; Video-assisted source separation <br>&#8226; Spatial audio object cod= ing <br>&#8226; Reverberant models for source separation <br>&#8226; Score-= informed source separation <br>&#8226; Language-informed speech separation = <br>&#8226; User-guided source separation <br>&#8226; Source separation inf= ormed by cover version <br>&#8226; Informed source separation applied to sp= eech, music or environmental signals <br>&#8226; &#8230; <br><br>----------= --------- <br>Guest Editors <br>Taylan Cemgil, Bogazici University, Turkey,= <br>Tuomas Virtanen, Tampere University of Technology, Finland, <br>Alexey= Ozerov, Technicolor, France, <br>Derry Fitzgerald, Dublin institute of Tec= hnology, Ireland, <br><br>Lead Guest Editor: <br>Ga=EBl Richard, Institut M= ines-T=E9l=E9com, T=E9l=E9com ParisTech, CNRS-LTCI, France.<o:p></o:p></p><= p class=3DMsoNormal style=3D'mso-margin-top-alt:auto;mso-margin-bottom-alt:= auto'><o:p>&nbsp;</o:p></p></div></body></html>= --_000_B02BDB2D74045345919286EDF0DA730A0854A8CC1BMOPESMBX01eut_--


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