CALL FOR PAPER
Special Issue of IEEE Transactions on Audio, Speech and Language
Processing
**SIGNAL MODELS AND REPRESENTATION OF MUSICAL AND ENVIRONMENTAL SOUNDS**
http://www.ewh.ieee.org/soc/sps/tap
http://www.ewh.ieee.org/soc/sps/tap/sp_issue/audioCFP.pdf
*-- Submission deadline: 15 December, 2008 --*
Notification of acceptance: 15 June, 2009
Final manuscript due: 1st July, 2009
Tentative publication date: 1st September, 2009
Guest editors
Dr. Bertrand David (Telecom ParisTech, France)
bertrand.david@telecom-paristech.fr
Dr. Laurent Daudet (UPMC University Paris 06, France)
daudet@lam.jussieu.fr
Dr. Masataka Goto (National Institute of Advanced Industrial Science and
Technology, Japan)
m.goto@aist.go.jp
Dr. Paris Smaragdis (Adobe Systems, Inc, USA)
paris@adobe.com
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The non-stationary nature, the richness of the spectra and the mixing of
diverse sources are common characteristics shared by musical and
environmental audio scenes. It leads to specific challenges of audio
processing tasks such as information retrieval, source separation,
analysis-transformation-synthesis and coding. When seeking to extract
information from musical or environmental audio signals, the time-varying
waveform or spectrum are often further analysed and decomposed into sound
elements. Two aims of this decomposition can be identified, which are
sometimes antagonist: to be together adapted to the particular properties
of the signal and to the targeted application. This special issue is
focused on how the choices of a low level representation (typically a
time-frequency distribution with or without probabilistic framework, with
or without perceptual considerations), a source model or a decomposition
technique may influence the overall performance.
Specific topics of interest include but are not limited to:
* factorizations of time-frequency distribution
* sparse representations
* Bayesian frameworks
* parametric modeling
* subspace-based methods for audio signals
* representations based on instrument or/and environmental sources signal
models
* sinusoidal modeling of non-stationary spectra (sinusoids, noise,
transients)
Typical applications considered are (non exclusively):
* source separation/recognition
* mid or high level features extraction (metrics, onsets, pitches, …)
* sound effects
* audio coding
* information retrieval
* audio scene structuring, analysis or segmentation
* ...
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