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Postdoctoral position in real-time music source separation
The METISS team at INRIA Rennes, France, is offering a postdoc position
in real-time music source separation in the context of a project with
Audionamix, the leading company in source separation (see details
below). Applications including a full resume, a letter of motivation and
up to three reference letters must be sent by email to the principal
investigator before October 1, 2010. Phone interviews of selected
candidates will be held during the first week of October.
TITLE: Real-time music source separation
DURATION: 2.5 years
RECRUITMENT DATE: as soon as possible and no later than January 1, 2011
SALARY: according to experience
PRINCIPAL INVESTIGATOR: Emmanuel Vincent (emmanuel.vincent@xxxxxxxx)
CO-PRINCIPAL INVESTIGATOR: Rémi Gribonval (remi.gribonval@xxxxxxxx)
DESCRIPTION OF THE PROJECT:
As a consequence of the ubiquity of 3D audio devices, music
professionals and listeners are expecting increasingly advanced
stereo-to-3D playback systems. While current systems rely on simple
spatial filtering algorithms, real-time access to individual sound
sources is necessary for improved spatialization and interaction.
Today's audio source separation algorithms cannot be used in this
context since they typically operate offline by learning source models
over the full signal duration.
This postdoctoral project aims to design real-time music source
separation algorithms. This work will be based on the state-of-the-art
"variance modeling" paradigm  making it possible to combine
alternative source models such as GMM and NMF currently at the core of
industrial source separation systems. Three challenges will be
investigated in particular:
- determining the best combination of models for the extraction of a
target class of sources given computation and parallelization constraints,
- proposing a general procedure for robust online learning of the model
parameters from small amounts of data,
- estimating advanced spatial parameters in addition to the source
directions of arrival, e.g. their distance to the microphones or the
room reverberation time, and exploiting them for dereverberation
Promising research tracks can be found in the literature about online
GMM or NMF learning [2,3] and variance-based reverberation modeling .
 A. Ozerov, E. Vincent and F. Bimbot, "A general modular framework
for audio source separation", in Proc. 9th Int. Conf. on Latent Variable
Analysis and Signal Separation (LVA/ICA), 2010.
 Y. Zhang and M.S. Scordilis, "Effective online unsupervised
adaptation of Gaussian mixture models and its application to speech
classification", Pattern Recognition Letters 29(6), 2008.
 B. Cao, D. Shen, J.-T. Sun, X. Wang, Q. Yang and Z. Chen, "Latent
factor detection and tracking with online non negative matrix
factorization", in Proc. International Joint Conferences on Artificial
Intelligence (IJCAI), 2007.
 N.Q.K. Duong, E. Vincent and R. Gribonval, "Under-determined
reverberant audio source separation using a full-rank spatial covariance
model", IEEE Transactions on Audio, Speech and Language Processing
INRIA, the French National Institute for Research in Computer Science
and Control plays a leading role in the development of Information
Science and Technology (IST) in Europe. The METISS team at INRIA Rennes
gathers a staff of 20 people focusing on audio signal processing research.
This position is part of the i3DMusic project supported by EUREKA aiming
to interactively respatialize mono or stereo music content in real time.
It will involve regular exchanges and collaboration with the project
coordinator Audionamix (http://www.audionamix.com/) in Paris and the
other partners Sonic Emotion (http://www.sonicemotion.com/) and EPFL in
Prospective candidates must hold or be about to defend a PhD in audio
signal processing. Proficient coding in Matlab or C++ is necessary.
Additional knowledge about musical audio, 3D audio rendering or parallel
computing would be an asset.
INRIA Rennes - Bretagne Atlantique
Campus de Beaulieu, 35042 Rennes cedex, France
Phone: +332 9984 2269 - Fax: +332 9984 7171