[AUDITORY] Deadline approaching - Workshop on Deep Learning for Music - Anchorage (Dorien Herremans )

Subject: [AUDITORY] Deadline approaching - Workshop on Deep Learning for Music - Anchorage From: Dorien Herremans <dorien.herremans@xxxxxxxx> Date: Wed, 22 Feb 2017 13:07:22 +0800 List-Archive:<http://lists.mcgill.ca/scripts/wa.exe?LIST=AUDITORY> --001a114916b82f3a240549177b1b 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)) 18-19 May, 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 music 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 <http://dorienherremans.com/dlm2017/dlm17template.zip> should be followed. 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 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 (such as Journal of New Music Research or IEEE Transactions on Neural Networks (tbc)). 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 Workshop on Deep Learning and Music <http://dorienherremans.com/dlm2017>, May'17 Anchorage, Alaska. --001a114916b82f3a240549177b1b Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable <div dir=3D"ltr">[apologies for cross-posting]= In= ternational Workshop on= Dee= p Learning for Music<= /p>In conjunction with the 2017 International= Joint Conference on Neural Networks (IJCNN 2017)) 18-19 May, Anchorage<a href= =3D"http://dorienherremans.com/dlm2017/" target=3D"_blank">More info</a></p= ><div style=3D"font-size:12.8px"> </div><div style=3D"font-size:12.8px">= <span= id=3D"m_231935395052702923gmail-m_-2010729269265642349gmail-m_-87458366615= 73943923gmail-m_-8644710822012710773gmail-m_-8952224694562584284gmail-m_-39= 49242688091976987gmail-docs-internal-guid-ccb3d90f-b5c5-44d1-09a9-a7f7a1107= 0e5">There has been tremendous interest in deep <sp= an class=3D"m_231935395052702923gmail-m_-2010729269265642349gmail-m_-874583= 6661573943923gmail-il">learning across many fields of study. Recentl= y, these techniques have gained popularity in the field of music. Projects = such as Magenta (Google's Brain Team's music generation project), J= ukedeck 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 compu= ters 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 ex= traction, emotion recognition, music recommendation, and automated music ge= neration. With this workshop we aim to advance the state-of-the-art i= n machine intelligence for music by bringing together researchers in the fi= eld 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.<div> </div> Topics<= /span> <= /p>Papers and a= bstracts on the application of deep learning techniques on music are welcomed, including but not lim= ited to: <ul style=3D"margin-top:0pt;margin-bottom:0pt"><li dir= =3D"ltr" style=3D"margin-left:15px;list-style-type:disc;font-size:14.6667px= ;background-color:transparent;vertical-align:baseline">Deep</span= > learning applications for computa= tional music research</li><li dir=3D"ltr" style=3D"margin-left:1= 5px;list-style-type:disc;font-size:14.6667px;background-color:transparent;v= ertical-align:baseline">Modeling hierarchical and long term m= usic structures using deep learning</sp= an></li><li dir=3D"ltr" style=3D"margin-left:15px;list-style-typ= e:disc;font-size:14.6667px;background-color:transparent;vertical-align:base= line">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"http://dorienhe= rremans.com/dlm2017/" style=3D"font-family:arial,sans-serif;font-size:small= ;text-align:center;white-space:normal" target=3D"_blank">More info</a></spa= n></div><div style=3D"font-size:12.8px"> Invited speakersInvited speakers= include Dr. Oriol Nieto (Pandor= a), Prof. Dr. Douglas Ec= k (the Head of the Google Magenta team) (tentatively confirme= d), and Dr. Kat Agres (A*STAR Institute of High Performance C= omputing). <div> </div></div><div= style=3D"font-size:12.8px"> Submiss= ions of PapersPapers</span= > of up to 5 pages using the following template are welcomed for a talk. Su= bmissions will be evaluated according to their originality, technical sound= ness, and relevance to the wor= kshop. The guidelines outlined in the workshop=E2=80=99s latex template [ dorienherremans. com/dlm2017/dlm17template. zip ]</fo= nt>  should be followed. Contributions should be in PDF format= and submitted to <a href=3D"mailto:d.herremans@xxxxxxxx" style=3D= "text-decoration:none" target=3D"_blank">d.herremans@xxxxxxxx<= /span></a> with the subject line: [DLM17 pap= er submission]. Submissions do not need to be anonymised. P= apers will be peer-reviewed and published in the proceedings = of the workshop. </span= > = Submissions of AbstractsStructured abstracts of max 2 pages can = be submitted for a shorter talk. The abstracts should follow the same template as the papers</= span> and will be included in the proceedings. Abstracts should be in PDF format and submitted to = <a href=3D"mailto:d.herremans@xxxxxxxx" style=3D"text-decoration:n= one" target=3D"_blank">d.herremans@xxxxxxxx</a> wi= th the subject line: [DLM17 ab= stract submission]. Abstracts will be peer-reviewed and included in th= e proceedings of the workshop<= /span>. Special Issue in Journal</s= pan>Authors will be invited to submit a full paper version of their extended abstract for a special issue in an indexed journal (su= ch as Journal of New Music Research or IEEE Transactions on Neural Networks= (tbc)). More details on this will be available soon. <br class=3D"m_231935395052702923gmail-m_-20= 10729269265642349gmail-m_-8745836661573943923gmail-m_-8644710822012710773gm= ail-m_-8952224694562584284gmail-m_-3949242688091976987gmail-Apple-interchan= ge-newline">Important DatesPaper Submission Deadline: February 28th</= span>Acceptance Notification: March= 12thFinal versions due: March 23, 2017= Workshop Date: one day during conference May 14-19, 2017</= span> Regist= ration Work= shop registration will be handled by the main conference, please che= ck IJCNN for more details. Organizers</= span>Dorien Herremans (Queen Mary University of London, UK)= Ching-Hua Chuan (University of North-Florida, US) <p= dir=3D"ltr" style=3D"line-height:1.38;margin-top:0pt;margin-bottom:0pt"><s= pan style=3D"font-size:14.6667px;color:rgb(68,68,68);font-weight:700;vertic= al-align:baseline">Programme Committee Dorien= Herremans (Queen Mary University of London, UK)Ching-Hua C= huan (University of North-Florida, US)Louis Bigo (Universit=C3=A9 Lille= 3, France)Maarten Grachten (Austrian Research = Institute for Artificial Intelligence, Austria)Sebastian St= ober (University of Potsdam, Germany) <a href=3D"http://dorie= nherremans.com/dlm2017/" style=3D"font-family:arial,sans-serif;font-size:sm= all;text-align:center;white-space:normal" target=3D"_blank">More info</a></= span></div><div> </div>-- <div class=3D"m_231935395052702923gmail_si= gnature"><div dir=3D"ltr"><div><div dir=3D"ltr"><div><div dir=3D"ltr" style= =3D"font-size:small">Dorien Herremans, PhD</div><div dir= =3D"ltr" style=3D"font-size:small">Marie-Curie Fellow</d= iv><div dir=3D"ltr"><a href=3D"http://dorienherremans.com/" target=3D"= _blank">http://dorienherremans.com</a> Queen Mary University of Lond= on School of Electronic Engineering and Computer Science<d= iv style=3D"font-size:small">C= 4DM - Centre for Digital Music, London</div><div> </div><div><fon= t size=3D"1"><a href=3D"http://dorienherremans.com/dlm2017" target=3D"_blan= k">Workshop on Deep Learning and Music</a>, May'17 Anchorage, Alaska.= =C2=A0</div></div></div></div></div></div></div> </div> --001a114916b82f3a240549177b1b--

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