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We call for submissions to our workshop "Machine Learning for Audio
Signal Processing (ML4Audio)" at NIPS 2017, Dec 8th in Los Angeles.
Apologies for the cross-posting:<br>
<br>
Audio signal processing is currently undergoing a paradigm change,
where data-driven machine learning is replacing hand-crafted feature
design. This has led some to ask whether audio signal processing is
still useful in the "era of machine learning." There are many
challenges, new and old, including the interpretation of learned
models in high dimensional spaces, problems associated with
data-poor domains, adversarial examples, high computational
requirements, and research driven by companies using large in-house
datasets that is ultimately not reproducible.<br>
<br>
ML4Audio (<a class="moz-txt-link-freetext" href="https://nips.cc/Conferences/2017/Schedule?showEvent=8790">https://nips.cc/Conferences/2017/Schedule?showEvent=8790</a>)
aims to promote progress, systematization, understanding, and
convergence of applying machine learning in the area of audio signal
processing. Specifically, we are interested in work that
demonstrates novel applications of machine learning techniques to
audio data, as well as methodological considerations of merging
machine learning with audio signal processing. We seek contributions
in, but not limited to, the following topics:<br>
- audio information retrieval using machine learning;<br>
- audio synthesis with given contextual or musical constraints using
machine learning;<br>
- audio source separation using machine learning;<br>
- audio transformations (e.g., sound morphing, style transfer) using
machine learning;<br>
- unsupervised learning, online learning, one-shot learning,
reinforcement learning, and incremental learning for audio;<br>
- applications/optimization of generative adversarial networks for
audio;<br>
- cognitively inspired machine learning models of sound cognition;<br>
- mathematical foundations of machine learning for audio signal
processing.<br>
<br>
ML4Audio will accept five kinds of submissions:<br>
1. novel unpublished work, including work-in-progress;<br>
2. recent work that has been already published or is in review
(please clearly refer to the primary publication);<br>
3. review-style papers;<br>
4. position papers;<br>
5. system demonstrations.<br>
<br>
Submissions: Extended abstracts as pdf in NIPS paper format, 2-4
pages, excluding references. Submissions do not need to be
anonymised. Submissions might be either accepted as talks or as
posters. Submission link:
<a class="moz-txt-link-freetext" href="https://easychair.org/conferences/?conf=ml4audio">https://easychair.org/conferences/?conf=ml4audio</a><br>
<br>
Publication: We are currently pursuing the organisation of a special
journal issue of selected papers from the workshop, but all works
presented at the workshop will be published online.<br>
<br>
Important Dates:<br>
Submission Deadline: October 20, 2017<br>
Acceptance Notification: October 31, 2017<br>
Camera Ready Submissions: November 30, 2017<br>
Workshop: Dec 8, 2017<br>
<br>
(Note that the main conference is sold out, but we have workshop
tickets reserved for presenters of accepted papers.)<br>
<br>
This workshop especially targets researchers, developers and
musicians in academia and industry in the area of MIR, audio
processing, hearing instruments, speech processing, musical HCI,
musicology, music technology, music entertainment, and composition.<br>
<br>
Invited Speakers:<br>
Karen Livescu (Toyota Technological Institute at Chicago)<br>
Sander Dieleman (Google DeepMind)<br>
Douglas Eck (Google Magenta)<br>
Marco Marchini (Spotify)<br>
N.N. (Pandora)<br>
<br>
Panel Discussion:<br>
Sepp Hochreiter (Johannes Kepler University Linz)<br>
Invited speakers<br>
Others to be decided<br>
<br>
ML4Audio Organisation Committee:<br>
- Hendrik Purwins, Aalborg University Copenhagen, Denmark
(<a class="moz-txt-link-abbreviated" href="mailto:hpu@create.aau.dk">hpu@create.aau.dk</a>)<br>
- Bob L. Sturm, Queen Mary University of London, UK
(<a class="moz-txt-link-abbreviated" href="mailto:b.sturm@qmul.ac.uk">b.sturm@qmul.ac.uk</a>)<br>
- Mark Plumbley, University of Surrey, UK (<a class="moz-txt-link-abbreviated" href="mailto:m.plumbley@surrey.ac.uk">m.plumbley@surrey.ac.uk</a>)<br>
<br>
PROGRAM COMMITTEE:<br>
Abeer Alwan (University of California, Los Angeles)<br>
Jon Barker (University of Sheffield)<br>
Sebastian Böck (Johannes Kepler University Linz)<br>
Mads Græsbøll Christensen (Aalborg University)<br>
Maximo Cobos (Universitat de Valencia)<br>
Sander Dieleman (Google DeepMind)<br>
Monika Dörfler (University of Vienna)<br>
Shlomo Dubnov (UC San Diego)<br>
Philippe Esling (IRCAM)<br>
Cédric Févotte (IRIT) <br>
Emilia Gómez (Universitat Pompeu Fabra) <br>
Emanuël Habets (International Audio Labs Erlangen)<br>
Jan Larsen (Danish Technical University) <br>
Marco Marchini (Spotify)<br>
Ricard Marxer (University of Toulon)<br>
Rafael Ramirez (Universitat Pompeu Fabra)<br>
Gaël Richard (TELECOM ParisTech) <br>
Fatemeh Saki (UT Dallas)<br>
Jan Schlüter (Austrian Research Institute for Artificial
Intelligence)<br>
Joan Serrà (Telefonica)<br>
Malcolm Slaney (Google)<br>
Emmanuel Vincent (INRIA Nancy)<br>
Gerhard Widmer (Austrian Research Institute for Artificial
Intelligence)<br>
Tao Zhang (Starkey Hearing Technologies)<br>
Others to be decided<br>
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--
Dr. Hendrik Purwins, Associate Professor, Dipl.-Math.
Audio Analysis Lab & Sound and Music Computing Group
Technical Faculty of IT and Design
Aalborg University Copenhagen
<a class="moz-txt-link-freetext" href="http://homes.create.aau.dk/hpu/">http://homes.create.aau.dk/hpu/</a>
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