[AUDITORY] Fwd: Workshop on Deep Learning for Music - Call for abstracts/papers (Dorien Herremans )

Subject: [AUDITORY] Fwd: Workshop on Deep Learning for Music - Call for abstracts/papers From: Dorien Herremans <dorien.herremans@xxxxxxxx> Date: Sun, 29 Jan 2017 23:24:02 +0800 List-Archive:<http://lists.mcgill.ca/scripts/wa.exe?LIST=AUDITORY> --94eb2c0b6c322d08ec05473d4b6e Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: quoted-printable [Apologies for cross posting] International Workshop on Deep Learning for Music In conjunction with the 2017 International Joint Conference on Neural Networks (IJCNN 2017)) 14-19 May (1 day), Anchorage More info <http://dorienherremans.com/dlm2017/> There has been tremendous interest in deep learning across many fields of study. Recently, these techniques have gained popularity in the field of music. Projects such as Magenta (Google's Brain Team's music generation project), Jukedeck and others testify to their potential. While humans can rely on their intuitive understanding of musical patterns and the relationships between them, it remains a challenging task for computers to capture and quantify musical structures. Recently, researchers have attempted to use deep learning models to learn features and relationships that allow us to accomplish tasks in music transcription, audio feature extraction, emotion recognition, music recommendation, and automated music generation. With this workshop we aim to advance the state-of-the-art in machine intelligence for music by bringing together researchers in the field of music and deep learning. This will enable us to critically review and discuss cutting-edge-research so as to identify grand challenges, effective methodologies, and potential new applications. Topics Papers and abstracts on the application of deep learning techniques on musi= c are welcomed, including but not limited to: - Deep learning applications for computational music research - Modeling hierarchical and long term music structures using deep learning - Modeling ambiguity and preference in music - Software frameworks and tools for deep learning in music More info <http://dorienherremans.com/dlm2017/> Invited speakers Invited speakers include Dr. Oriol Nieto (*Pandora*), Prof. Dr. Douglas Eck (the Head of the *Google* Magenta team) (tentatively confirmed), and Dr. Kat Agres (*A*STAR* Institute of High Performance Computing). Submissions of Papers Papers of up to 5 pages using the following template are welcomed for a talk. Submissions will be evaluated according to their originality, technical soundness, and relevance to the workshop. The guidelines outlined in the workshop=E2=80=99s latex template should be followed (the template w= ill be available shortly). Contributions should be in PDF format and submitted to d.herremans@xxxxxxxx with the subject line: [DLM17 paper submission]. Submissions do not need to be anonymised. Papers will be peer-reviewed and published in the proceedings of the workshop. Submissions of Abstracts Structured abstracts of max 2 pages can be submitted for a shorter talk. The abstracts should follow the same template as the papers (which will be available shortly) and will be included in the proceedings. Abstracts should be in PDF format and submitted to d.herremans@xxxxxxxx with the subject line: [DLM17 abstract submission]. Abstracts will be peer-reviewed and included in the proceedings of the workshop. Special Issue in Journal Authors will be invited to submit a full paper version of their extended abstract for a special issue in an indexed journal. More details on this will be available soon. Important Dates Paper Submission Deadline: February 28th Acceptance Notification: March 12th Final versions due: March 23, 2017 Workshop Date: one day during conference May 14-19, 2017 Registration Workshop registration will be handled by the main conference, please check IJCNN for more details. Organizers Dorien Herremans (Queen Mary University of London, UK) Ching-Hua Chuan (University of North-Florida, US) Programme Committee Dorien Herremans (Queen Mary University of London, UK) Ching-Hua Chuan (University of North-Florida, US) Louis Bigo (Universit=C3=A9 Lille 3, France) Maarten Grachten (Austrian Research Institute for Artificial Intelligence, Austria) Sebastian Stober (University of Potsdam, Germany) More info <http://dorienherremans.com/dlm2017/> --=20 Dorien Herremans, PhD Marie-Curie Fellow http://dorienherremans.com Queen Mary University of London School of Electronic Engineering and Computer Science C4DM - Centre for Digital Music, London --94eb2c0b6c322d08ec05473d4b6e Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable <div dir=3D"ltr"><div class=3D"gmail_quote"> <div dir=3D"ltr">[Apolog= ies for cross posting] = International Workshop on Deep Learning</span= > for Music= In conjunction with the 2017 International Joint Conference on= Neural Networks (IJCNN 2017)) 14-19 May (1 day), Anchorage<a href=3D"http://dorie= nherremans.com/dlm2017/" target=3D"_blank">More info</a><div> </div>= <div>= There has been tremendous interest in deep learning across many fields of study. Recently, these techniq= ues have gained popularity in the field of music. Projects such as Magenta (Google's Brain Te= am's music generat= ion project), Jukedeck and others testify to their potential.<br= >While humans can rely on their intuitive understanding of <s= pan class=3D"m_-483651031487167565gmail-il">musical patterns and the= relationships between them, it remains a challenging task for computers to= capture and quantify musical= structures. Recently, researchers have attempted to use deep learning models to learn features and relationships that allow us to acc= omplish tasks in music= transcription, audio feature extraction, emotion recognition, music recommendation, and automat= ed music generation. <= /span> With this workshop we aim to advance the state-of-the-art in machine = intelligence for music= by bringing together researchers in the field of music and deep learning= . This will enable us to critically review and discuss cutting-edge-= research so as to identify grand challenges, effective methodologies, and p= otential new applications.<div> </div> Topics= Papers and abstracts on the application of deep learning techniques on music are welcomed, including but not limited to: </s= pan><ul style=3D"margin-top:0pt;margin-bottom:0pt"><li dir=3D"ltr" styl= e=3D"margin-left:15px;list-style-type:disc;font-size:14.6667px;background-c= olor:transparent;vertical-align:baseline">Deep learning applications for computational music research</li><li dir=3D= "ltr" style=3D"margin-left:15px;list-style-type:disc;font-size:14.6667px;ba= ckground-color:transparent;vertical-align:baseline">Modeling = hierarchical and long term mu= sic structures using d= eep learning</s= pan></li><li dir=3D"ltr" style=3D"margin-left:15px;list-style-type:disc= ;font-size:14.6667px;background-color:transparent;vertical-align:baseline">= = Modeling ambiguity and preference in music</li><li dir=3D"ltr" style=3D"= margin-left:15px;list-style-type:disc;font-size:14.6667px;background-color:= transparent;vertical-align:baseline">Software frameworks and = tools for deep learning in music</li></ul><a href=3D"ht= tp://dorienherremans.com/dlm2017/" style=3D"font-family:arial,sans-serif;fo= nt-size:small;text-align:center;white-space:normal" target=3D"_blank">More = info</a></div><div> Invited speakers<s= pan style=3D"font-size:14.6667px">Invited speakers include Dr. Oriol Nieto = (Pandora), Prof. Dr. Douglas Eck (the Head of the = Google Magenta team) (tentatively confirmed), and Dr. Kat Agres (<i= >A*STAR Institute of High Performance Computing). <di= v> </div></div><div> <span= style=3D"font-size:14.6667px;color:rgb(68,68,68);font-weight:700;vertical-= align:baseline">Submissions of PapersPa= pers of up to 5 pages using the following template are welcomed for a talk.= Submissions will be evaluated according to their originality, technical so= undness, and relevance to the workshop. The guidelines outlined in the workshop=E2=80=99s latex template should be foll= owed (the template will be available shortly). Contributions should be in P= DF format and submitted to <a href=3D"mailto:d.herremans@xxxxxxxx"= style=3D"text-decoration:none" target=3D"_blank">d.herremans@xxxxxxxx= ul.ac.uk</a> with the subject line: [DLM17 paper submission]. <= /span>Submissio= ns do not need to be anonymised. Papers will be peer-r= eviewed and published in the proceedings of the workshop. Submissions o= f AbstractsStructured abstracts of max = 2 pages can be submitted for a shorter talk. The abstracts should follow th= e same template as the papers (which will be available shortly) and will be= included in the proceedings. Abstracts should be in PDF format and submitt= ed to <a href=3D"mailto:d.herremans@xxxxxxxx" style=3D"text-decora= tion:none" target=3D"_blank">d.herremans@xxxxxxxx</a><s= pan style=3D"font-size:14.6667px;color:rgb(68,68,68);vertical-align:baselin= e"> with the subject line: [DLM17 abstract submission]. Abstracts will be peer-reviewed and included in the proceedings of the <= span class=3D"m_-483651031487167565gmail-il">workshop. <p= dir=3D"ltr" style=3D"line-height:1.38;margin-top:0pt;margin-bottom:0pt"><b= r>Special Issue in JournalAuthor= s will be invited to submit a full paper version of their extended abstract= for a special issue in an indexed journal. More details on this will be av= ailable soon. Important Dates</= span>Paper Submission Deadline: Feb= ruary 28thAcceptance Notification: </sp= an>March 12thFinal versions due: Ma= rch 23, 2017Workshop Date: one day during conference May = 14-19, 2017 Registration Workshop registration will be handled by the main conferen= ce, please check IJCNN for more details. OrganizersDorien Herremans (Queen Mary University of Lond= on, UK)Ching-Hua Chuan (University of North-Florida, US)</s= pan> Programme Committee </p= >Dorien Herremans (Queen Mary University of London, UK)<spa= n style=3D"font-size:14.6667px;color:rgb(68,68,68);vertical-align:baseline"= >Ching-Hua Chuan (University of North-Florida, US)Louis Bigo (Universit= =C3=A9 Lille 3, France)Maarten Grachten (Austri= an Research Institute for Artificial Intelligence, Austria)<span= style=3D"font-size:14.6667px;color:rgb(84,84,84);vertical-align:baseline">= Sebastian Stober (University of Potsdam, Germany) <a href=3D"= http://dorienherremans.com/dlm2017/" style=3D"font-family:arial,sans-serif;= font-size:small;text-align:center;white-space:normal" target=3D"_blank">Mor= e info</a><div class=3D"m_-483651031487167565gmail-yj6qo m_-483651031487167= 565gmail-ajU" style=3D"margin:2px 0px 0px"><div id=3D"m_-483651031487167565= gmail-:1ns" class=3D"m_-483651031487167565gmail-ajR"><img class=3D"m_-48365= 1031487167565gmail-ajT" src=3D"https://ssl.gstatic.com/ui/v1/icons/mail/ima= ges/cleardot.gif"></div></div> </di= v><div> </div><div> </div><spa= n class=3D"HOEnZb"><b= r class=3D"m_-483651031487167565gmail-m_7715901087939620715gmail-Apple-inte= rchange-newline" style=3D"font-size:12.8px">--=C2=A0 <div class=3D"m_-4836510314= 87167565gmail-m_7715901087939620715gmail-m_-3949242688091976987gmail_signat= ure" style=3D"font-size:12.8px"><div dir=3D"ltr"><div dir=3D"ltr"><div dir= =3D"ltr"><div dir=3D"ltr">Dorien Herremans, PhD</div><di= v dir=3D"ltr">Marie-Curie Fellow</div><div dir=3D"ltr"><= span style=3D"font-size:12.8px;font-family:tahoma,sans-serif"><a href=3D"http://dorienherremans.com/" target=3D"_blank">http://dorien= herremans.com</a> Queen Mary University of London School of Elect= ronic Engineering and Computer Science<div>C4DM - Centre for Digital=C2=A0Music, London</div><div> </div></div></div></div></d= iv></div><div> </div> </div> </div> </div> --94eb2c0b6c322d08ec05473d4b6e--

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