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

Subject: Call for Papers: Special Issue on Informed Acoustic Source Separation; EURASIP Journal on Advances in Signal Processing From: Ozerov Alexey <Alexey.Ozerov@xxxxxxxx> Date: Fri, 7 Dec 2012 10:14:23 +0100 List-Archive:<http://lists.mcgill.ca/scripts/wa.exe?LIST=AUDITORY> --_000_FABFECD6AE260643A25A5C6F611BCC0F1A2628EE34MOPESMBX01eut_ Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable We apologize for cross-distribution and multiple copies. *************************************************** 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 s= ignals * ... ------------------- 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_FABFECD6AE260643A25A5C6F611BCC0F1A2628EE34MOPESMBX01eut_ 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></style></head><body lang=3DEN-US link=3Dblue vli= nk=3Dpurple><div class=3DWordSection1><address>We apologize for cross-distr= ibution and multiple copies.<o:p></o:p></address><pre>*********************= ******************************<o:p></o:p></pre>CALL FOR PAPERS EURASIP Journal on Advance= s in Signal  Processing Special Issue on Informed Acoustic Sour= ce Separation The complete call of papers is accessible at: <= a href=3D"http://asp.eurasipjournals.com/sites/10233/pdf/H9386_DF_CFP_EURAS= IP_JASP_A4_3.pdf">http://asp.eurasipjournals.com/sites/10233/pdf/H9386_DF_C= FP_EURASIP_JASP_A4_3.pdf</a> DEADLINE: PAPER SUBMISSION: 31st May 20= 13 -----------------------------------------------------------------= ------------------------------------- Short Description The propo= sed topic of this special issue is informed acoustic source separation. As = source separation has long become a field of interest in the signal process= ing community, recent works increasingly point out the fact that separation= can only be reliably achieved in real-world use cases when accurate prior = information can be successfully incorporated. Informed separation algorithm= s can be characterized by the fact that case-specific prior knowledge is ma= de available to the algorithm for processing. In this respect, they contras= t with blind methods for which no specific prior information is available.<= br>Following on the success of the special session on the same topic in EUS= IPCO 2012 at Bucharest, we would like to present recent methods, discuss th= e trends and perspectives of this domain and to draw the attention of the s= ignal processing community to this important problem and its potential appl= ications. We are interested in both methodological advances and application= s.  Topics of interest include (but are not limited to): &#8226= ;    Sparse decomposition methods •   &nb= sp;Subspace learning methods for sparse decomposition • &nbsp= ;  Non-negative matrix / tensor factorization •   &= nbsp;Robust principal component analysis •    Proba= bilistic latent component analysis •    Independent= component analysis •    Multidimensional component= analysis •    Multimodal source separation &#82= 26;    Video-assisted source separation • &nbs= p;  Spatial audio object coding •    Reverber= ant models for source separation •    Score-informe= d source separation •    Language-informed speech s= eparation •    User-guided source separation &#8= 226;    Source separation informed by cover version &#822= 6;    Informed source separation applied to speech, music or= environmental signals •    … --------= ----------- Guest Editors Taylan Cemgil, Bogazici University, Turkey,= Tuomas Virtanen, Tampere University of Technology, Finland,  = Alexey Ozerov, Technicolor, France,  Derry Fitzgerald, Dublin inst= itute of Technology, Ireland,  Lead Guest Editor: Ga=EBl Ri= chard, Institut Mines-T=E9l=E9com, T=E9l=E9com ParisTech, CNRS-LTCI, France= ,  <o:p></o:p><o:p> </o:p><= /span></div></body></html>= --_000_FABFECD6AE260643A25A5C6F611BCC0F1A2628EE34MOPESMBX01eut_--

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