Subject: [machinelistening] 3rd Call for Papers: Special Issue on Informed From: Ozerov Alexey <Alexey.Ozerov@xxxxxxxx> Date: Mon, 13 May 2013 11:59:36 +0200 List-Unsubscribe:<http://groups.google.com/group/machinelistening/subscribe?hl=en_US>,--_000_B02BDB2D74045345919286EDF0DA730A086E31DE17MOPESMBX01eut_ Content-Type: text/plain; charset=ISO-8859-1 Content-Transfer-Encoding: quoted-printable We apologize for cross-distribution and multiple copies. *************************************************** 3rd 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 * Probabilisti= c latent component analysis * Independent component analysis * Multidimensi= onal component analysis * Multimodal source separation * Video-assisted sou= rce separation * Spatial audio object coding * Reverberant models for sourc= e 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 envi= ronmental signals * ... ------------------- Guest Editors Taylan Cemgil, Bogazici University, Turkey, Tuomas Virtanen, Tampere Univer= sity of Technology, Finland, Alexey Ozerov, Technicolor, France, Derry Fitz= gerald, Dublin institute of Technology, Ireland, Lead Guest Editor: Ga=EBl Richard, Institut Mines-T=E9l=E9com, T=E9l=E9com ParisTech, CNRS-LTC= I, France. --=20 You received this message because you are subscribed to the Google Groups "= Machine Listening" group. To unsubscribe from this group and stop receiving emails from it, send an e= mail to machinelistening+unsubscribe@xxxxxxxx For more options, visit https://groups.google.com/groups/opt_out. --_000_B02BDB2D74045345919286EDF0DA730A086E31DE17MOPESMBX01eut_ 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;} @xxxxxxxx {font-family:Consolas; panose-1:2 11 6 9 2 2 4 3 2 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;} p.MsoPlainText, li.MsoPlainText, div.MsoPlainText {mso-style-priority:99; mso-style-link:"Plain Text Char"; margin:0cm; margin-bottom:.0001pt; font-size:10.5pt; font-family:Consolas;} span.EmailStyle17 {mso-style-type:personal-compose; font-family:"Calibri","sans-serif"; color:windowtext;} span.PlainTextChar {mso-style-name:"Plain Text Char"; mso-style-priority:99; mso-style-link:"Plain Text"; font-family:Consolas;} .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=3DMsoPlainText>We apologize = for cross-distribution and multiple copies.<o:p></o:p></p><p class=3DMsoPla= inText><o:p> </o:p></p><p class=3DMsoPlainText>***********************= ****************************<o:p></o:p></p><p class=3DMsoPlainText><o:p>&nb= sp;</o:p></p><p class=3DMsoPlainText>3rd CALL FOR PAPERS<o:p></o:p></p><p c= lass=3DMsoPlainText><o:p> </o:p></p><p class=3DMsoPlainText>EURASIP Jo= urnal on Advances in Signal Processing Special Issue on Informed Acoustic S= ource Separation<o:p></o:p></p><p class=3DMsoPlainText><o:p> </o:p></p= ><p class=3DMsoPlainText>The complete call of papers is accessible at:<o:p>= </o:p></p><p class=3DMsoPlainText><a href=3D"http://asp.eurasipjournals.com= /sites/10233/pdf/H9386_DF_CFP_EURASIP_JASP_A4_3.pdf">http://asp.eurasipjour= nals.com/sites/10233/pdf/H9386_DF_CFP_EURASIP_JASP_A4_3.pdf</a><o:p></o:p><= /p><p class=3DMsoPlainText><o:p> </o:p></p><p class=3DMsoPlainText>DEA= DLINE: PAPER SUBMISSION: 31st May 2013<o:p></o:p></p><p class=3DMsoPlainTex= t><o:p> </o:p></p><p class=3DMsoPlainText>----------------------------= --------------------------------------------------------------------------<= o:p></o:p></p><p class=3DMsoPlainText>Short Description<o:p></o:p></p><p cl= ass=3DMsoPlainText><o:p> </o:p></p><p class=3DMsoPlainText>The propose= d topic of this special issue is informed acoustic source separation. As so= urce separation has long become a field of interest in the signal processin= g community, recent works increasingly point out the fact that separation c= an only be reliably achieved in real-world use cases when accurate prior in= formation can be successfully incorporated. Informed separation algorithms = can be characterized by the fact that case-specific prior knowledge is made= available to the algorithm for processing. In this respect, they contrast = with blind methods for which no specific prior information is available.<o:= p></o:p></p><p class=3DMsoPlainText>Following on the success of the special= session on the same topic in EUSIPCO 2012 at Bucharest, we would like to p= resent recent methods, discuss the trends and perspectives of this domain a= nd to draw the attention of the signal processing community to this importa= nt problem and its potential applications. We are interested in both method= ological advances and applications. Topics of interest include (but are not= limited to):<o:p></o:p></p><p class=3DMsoPlainText><o:p> </o:p></p><p= class=3DMsoPlainText>• Sparse decomposition methods<o:p></o:p></p><p= class=3DMsoPlainText>• Subspace learning methods for sparse decompos= ition • Non-negative matrix / tensor factorization • Robust pri= ncipal component analysis • Probabilistic latent component analysis &= #8226; Independent component analysis • Multidimensional component an= alysis • Multimodal source separation • Video-assisted source s= eparation • Spatial audio object coding • Reverberant models fo= r source separation • Score-informed source separation • Langua= ge-informed speech separation • User-guided source separation •= Source separation informed by cover version • Informed source separa= tion applied to speech, music or environmental signals • …<o:p>= </o:p></p><p class=3DMsoPlainText><o:p> </o:p></p><p class=3DMsoPlainT= ext>-------------------<o:p></o:p></p><p class=3DMsoPlainText>Guest Editors= <o:p></o:p></p><p class=3DMsoPlainText>Taylan Cemgil, Bogazici University, = Turkey, Tuomas Virtanen, Tampere University of Technology, Finland, Alexey = Ozerov, Technicolor, France, Derry Fitzgerald, Dublin institute of Technolo= gy, Ireland,<o:p></o:p></p><p class=3DMsoPlainText><o:p> </o:p></p><p = class=3DMsoPlainText>Lead Guest Editor:<o:p></o:p></p><p class=3DMsoPlainTe= xt>Ga=EBl Richard, Institut Mines-T=E9l=E9com, T=E9l=E9com ParisTech, CNRS-= LTCI, France.<o:p></o:p></p><p class=3DMsoNormal><o:p> </o:p></p><p cl= ass=3DMsoNormal><o:p> </o:p></p></div></body></html> <p></p> -- <br /> You received this message because you are subscribed to the Google Groups &= quot;Machine Listening" group.<br /> To unsubscribe from this group and stop receiving emails from it, send an e= mail to machinelistening+unsubscribe@xxxxxxxx<br /> For more options, visit <a href=3D"https://groups.google.com/groups/opt_out= ">https://groups.google.com/groups/opt_out</a>.<br /> <br /> <br /> --_000_B02BDB2D74045345919286EDF0DA730A086E31DE17MOPESMBX01eut_--