[AUDITORY] CFP: ML4Audio @ NIPS2017

[Hendrik Purwins <hpurwins@xxxxxxxxx>]

Apologies for cross-posting:

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.

ML4Audio (https://nips.cc/Conferences/2017/Schedule?showEvent=8790) 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:
- audio information retrieval using machine learning;
- audio synthesis with given contextual or musical constraints using 
machine learning;
- audio source separation using machine learning;
- audio transformations (e.g., sound morphing, style transfer) using 
machine learning;
- unsupervised learning, online learning, one-shot learning, 
reinforcement learning, and incremental learning for audio;
- applications/optimization of generative adversarial networks for audio;
- cognitively inspired machine learning models of sound cognition;
- mathematical foundations of machine learning for audio signal processing.

ML4Audio will accept five kinds of submissions:
1. novel unpublished work, including work-in-progress;
2. recent work that has been already published or is in review (please 
clearly refer to the primary publication);
3. review-style papers;
4. position papers;
5. system demonstrations.

Submission format: 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. If 
accepted, final papers must be uploaded on arxiv.org.

Submission link: https://easychair.org/conferences/?conf=ml4audio

Important Dates:
Submission Deadline: October 20, 2017
Acceptance Notification: October 31, 2017
Camera Ready Submissions: November 30, 2017
Workshop: Dec 8, 2017

(Note that the main conference is sold out already. Presenters of 
accepted workshop papers will still be able to register for the workshops.)

This workshop especially targets researchers, developers and musicians 
in academia and industry in the area of MIR, audio processing, speech 
processing, musical HCI, musicology, music technology, music 
entertainment, and composition.

Invited Speakers:
Sander Dieleman (Google DeepMind)
Douglas Eck (Google Magenta)
Marco Marchini (Spotify)
Others to be decided

Panel Discussion:
Sepp Hochreiter (Johannes Kepler University Linz),
Invited speakers
Others to be decided

ML4Audio Organisation Committee:
- Hendrik Purwins, Aalborg University Copenhagen, Denmark 
(hpu@xxxxxxxxxxxxx)
- Bob L. Sturm, Queen Mary University of London, UK (b.sturm@xxxxxxxxxx)
- Mark Plumbley, University of Surrey, UK (m.plumbley@xxxxxxxxxxxx)

PROGRAM COMMITTEE:
Sebastian Böck (Johannes Kepler University Linz)
Matthias Dorfer (Johannes Kepler University Linz)
Monika Dörfler (University of Vienna)
Shlomo Dubnov (UC San Diego)
Philippe Esling (IRCAM)
Cédric Févotte (IRIT)
Mads Græsbøll (Aalborg University)
Emilia Gómez (Universitat Pompeu Fabra)
Jan Larsen (Danish Technical University)
Marco Marchini (Spotify)
Rafael Ramirez (Universitat Pompeu Fabra)
Gaël Richard (TELECOM ParisTech)
Jan Schlüter (Austrian Research Institute for Artificial Intelligence)
Joan Serrà (Telefonica)
Malcolm Slaney (Google)
Gerhard Widmer (Austrian Research Institute for Artificial Intelligence)
Others to be decided