Subject: [AUDITORY] CfP: Applied Sciences Special Issue on Deep Learning for Applications in Acoustics: Modeling, Synthesis, and Listening (deadline extended) From: Juhan Nam <juhan@xxxxxxxx> Date: Thu, 2 Apr 2020 14:37:50 -0400 List-Archive:<http://lists.mcgill.ca/scripts/wa.exe?LIST=AUDITORY>--000000000000bf22be05a2531985 Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: quoted-printable [apologies for the cross posting, please circulate widely] Dear All, I would like to announce that the deadline for the Special Issue entitled "Deep Learning for Applications in Acoustics: Modeling, Synthesis, and Listening" in the open-access journal MDPI Applied Sciences has been extended to Jun 30, 2020 given the unfortunate circumstances that may affect your research. In this special issue, we welcome the submission of papers dealing with novel computational methods involving modeling, parametrization and knowledge extraction from acoustic data. The considered topics include, e.g.: - Applications of deep learning to sound synthesis - Control and estimation problems in physical modeling - Intelligent music production and novel digital audio effects - Representation learning and/or transfer of musical composition and performance characteristics including, timbre, style and playing technique - Analysis and modeling of acoustic phenomena including musical acoustics, speech signals, room acoustics, environmental, ecological, medical and machine sounds - Machine listening and perception models inspired by human hearing - Application of deep learning to wave propagation problems in fluids and solids Again, the deadline for full manuscript submission is 30 June, 2020. Please, see the details at this link: https://www.mdpi.com/journal/applsci/special_issues/Machine_Learning_Acoust= ical_Problems Kind regards, Guest Editors Dr. Leonardo Gabrielli, Department of Information Engineering, Universit=C3= =A0 Politecnica delle Marche (UNIVPM), Italy Dr. George Fazekas, Center for Digital Music (C4DM), Queen's Mary University, London, UK Dr. Juhan Nam, Korea Advanced Institute of Science and Technology (KAIST), Korea --000000000000bf22be05a2531985 Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable <div dir=3D"ltr">[apologies for the cross posting, please circulate widely]= <br><br>Dear All,<br><br>I would like to announce that the deadline for the= Special Issue entitled "Deep Learning for Applications in Acoustics: = Modeling, Synthesis, and Listening" in the open-access journal MDPI Ap= plied Sciences has been extended to Jun 30, 2020 given the unfortunate circ= umstances that may affect your research. <br>=C2=A0 <br>In this special iss= ue, we welcome the submission of papers dealing with novel computational me= thods involving modeling, parametrization and knowledge extraction from aco= ustic data. The considered topics include, e.g.:<br><br>- Applications of d= eep learning to sound synthesis<br>- Control and estimation problems in phy= sical modeling<br>- Intelligent music production and novel digital audio ef= fects<br>- Representation learning and/or transfer of musical composition a= nd performance characteristics including, timbre, style and playing techniq= ue<br>- Analysis and modeling of acoustic phenomena including musical acous= tics, speech signals, room acoustics, environmental, ecological, medical an= d machine sounds<br>- Machine listening and perception models inspired by h= uman hearing<br>- Application of deep learning to wave propagation problems= in fluids and solids<br><br><br>Again, the deadline for full manuscript su= bmission is 30 June, 2020. Please, see the details at this link: <a href=3D= "https://www.mdpi.com/journal/applsci/special_issues/Machine_Learning_Acous= tical_Problems">https://www.mdpi.com/journal/applsci/special_issues/Machine= _Learning_Acoustical_Problems</a> <br><br>Kind regards, <br><br>Guest Edito= rs<br><br>Dr. Leonardo Gabrielli, Department of Information Engineering, Un= iversit=C3=A0 Politecnica delle Marche (UNIVPM), Italy<br>Dr. George Fazeka= s, Center for Digital Music (C4DM), Queen's Mary University, London, UK= <br>Dr. Juhan Nam, Korea Advanced Institute of Science and Technology (KAIS= T), Korea<br></div> --000000000000bf22be05a2531985--