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

Subject: [AUDITORY] Workshop on Deep Learning for Music - Call for abstracts/papers From: Dorien Herremans <dorien.herremans@xxxxxxxx> Date: Tue, 24 Jan 2017 13:02:10 +0800 List-Archive:<http://lists.mcgill.ca/scripts/wa.exe?LIST=AUDITORY> --001a114c2202fa2bf60546d005ed 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 --=20 Dorien Herremans <http://dorienherremans.com/dlm2017/> <http://dorienherremans.com/dlm2017/> <http://dorienherremans.com/dlm2017/> --001a114c2202fa2bf60546d005ed Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable <div dir=3D"ltr">[Ap= ologies for cross posting] <= /span>International Wo= rkshop on Deep Learning for MusicIn conjunction with the 2017 International Joint Conference on Ne= ural Networks (IJCNN 2017)) 14-19 May (1 day), Anchorage<a href=3D"http://dorienhe= rremans.com/dlm2017/" target=3D"_blank">More info</a><div> </div><di= v><sp= an id=3D"gmail-m_7715901087939620715gmail-m_-3949242688091976987gmail-docs-= internal-guid-ccb3d90f-b5c5-44d1-09a9-a7f7a11070e5">There has= been tremendous interest in deep learning across many fields of study. Recently, thes= e techniques have gained popularity in the field of music. Projects such as Magenta (Google's Brain Team's <sp= an class=3D"gmail-il">music generation project), Jukedeck and others= testify to their potential. While humans can r= ely on their intuitive understanding of musical</s= pan> 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 t= o learn features and relationships that all= ow us to accomplish tasks in music transcri= ption, audio feature extraction, emotion recognition, music recommendation, and automated mus= ic generation. With this workshop we aim to advance the state-of-the-art in machin= e intelligence for music by bringing togeth= er researchers in the field of music and <s= pan class=3D"gmail-il">deep learning= . This will enable us to critically review and discuss cutting-edge-researc= h so as to identify grand challenges, effective methodologies, and potentia= l new applications.<div> </div> Topic= s </span= >Papers and abstracts on the application of deep learning techniques on <span= class=3D"gmail-il">music are welcomed, including but not limited 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;backgro= und-color:transparent;vertical-align:baseline">Deep learning application= s for computational music research</= p></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 hierarchical and long term music<= /span> structures using deep learning</li><li dir=3D"ltr" style=3D"margin-l= eft:15px;list-style-type:disc;font-size:14.6667px;background-color:transpar= ent;vertical-align:baseline">Modeling ambiguity and preferenc= e in music</li><li dir=3D"ltr" s= tyle=3D"margin-left:15px;list-style-type:disc;font-size:14.6667px;backgroun= d-color:transparent;vertical-align:baseline">Software framewo= rks and tools for deep learning in music</l= i></ul><a href=3D"http://dorienherremans.com/dlm2017/" target=3D"_blank" st= yle=3D"font-family:arial,sans-serif;font-size:small;text-align:center;white= -space:normal">More info</a></div><div> Invited speakers<sp= an style=3D"font-size:14.6667px">Invited speakers include Dr. Oriol Nieto (= Pandora), Prof. Dr. Douglas Eck (the Head of the G= oogle Magenta team) (tentatively confirmed), and Dr. Kat Agres (= A*STAR Institute of High Performance Computing). <div= > </div></div><div> Submissions of PapersPap= ers of up to 5 pages using the following template are welcomed for a talk. = Submissions will be evaluated according to their originality, technical sou= ndness, and relevance to the workshop. The = guidelines outlined in the workshop=E2=80= =99s latex template should be followed (the template will be available shor= tly). Contributions should be in PDF format and submitted to <a href= =3D"mailto:d.herremans@xxxxxxxx" target=3D"_blank" style=3D"text-decorati= on:none">d.herremans@xxxxxxxx</a> with the subject= line: [DLM17 paper submission]. Submissions do not need to be anonymised. <= span style=3D"font-size:14.6667px;background-color:transparent;vertical-ali= gn:baseline">Papers will be peer-reviewed and published in the proceedings = of the workshop. = Submissions of AbstractsStructured abst= racts of max 2 pages can be submitted for a shorter talk. The abstracts sho= uld follow the same template as the papers (which will be available shortly= ) and will be included in the proceedings. Abstracts should be in PDF forma= t and submitted to <a href=3D"mailto:d.herremans@xxxxxxxx" target= =3D"_blank" style=3D"text-decoration:none">d.herremans@xxxxxxxx= k</a> with the subject line: [DLM17 abstract submission]. </spa= n>Abstracts will be peer-reviewed and included in the proceed= ings of the workshop. <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">Special Issue in JournalAuthors will be= invited to submit a full paper version of their extended abstract for a sp= ecial issue in an indexed journal. More details on this will be available s= oon. Important Dates= Paper Submission Deadline: February 28thAcceptance Notification: March 12th</p= >Final versions due: March 23, 2017Workshop Date: one day dur</sp= an>ing conference May 14-19, 2017 Registration Workshop registration will be handled by the main co= nference, please check IJCNN for more details. OrganizersDorien Herremans (Queen Mary University= of London, UK)Ching-Hua Chuan (University of North-Florida= , US) Programme Committee </= span>Dorien Herremans (Queen Mary University of London, UK)= Ching-Hua Chuan (University of North-Florida, US)Louis Bigo (U= niversit=C3=A9 Lille 3, France)Maarten Grachten (<sp= an style=3D"font-size:14.6667px;color:rgb(84,84,84);vertical-align:baseline= ">Austrian Research Institute for Artificial Intelligence, Austria)<= /p>Sebastian Stober (University of Potsdam, Germany) <a = href=3D"http://dorienherremans.com/dlm2017/" target=3D"_blank" style=3D"fon= t-family:arial,sans-serif;font-size:small;text-align:center;white-space:nor= mal">More info <div> </div>-- <div class=3D"gmail_s= ignature" data-smartmail=3D"gmail_signature">Dorien Herremans </div> </a></div><div><a href=3D"http://dorienherremans.com/dlm2017/" targe= t=3D"_blank" style=3D"font-family:arial,sans-serif;font-size:small;text-ali= gn:center;white-space:normal">= </a></div><a href=3D"http://dorienherremans.com/dlm2017/"= target=3D"_blank" style=3D"font-family:arial,sans-serif;font-size:small;te= xt-align:center;white-space:normal"> </a></div> --001a114c2202fa2bf60546d005ed--

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DAn Ellis <dpwe@ee.columbia.edu>
Electrical Engineering Dept., Columbia University