Thursday, January 19, 2017

[DMANET] Workshop on Deep Learning for Music - Call for Abstracts/papers

International Workshop on Deep Learning for Music

In conjunction with the 2017 International Joint Conference on Neural

(IJCNN 2017))

14-19 May (1 day), Anchorage

More info <>

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.


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 <>

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's latex template
<> should be followed.
Contributions should be in PDF format and submitted to 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 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


Workshop registration will be handled by the main conference, please check
IJCNN for more details.


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 (Université Lille 3, France)

Maarten Grachten (Austrian Research Institute for Artificial Intelligence,

Sebastian Stober (University of Potsdam, Germany)

More info

Dorien Herremans

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