CfP: Special Issue on Statistical and Perceptual Audio Processing (Dan Ellis )


Subject: CfP: Special Issue on Statistical and Perceptual Audio Processing
From:    Dan Ellis  <dpwe(at)EE.COLUMBIA.EDU>
Date:    Thu, 20 Jan 2005 10:59:55 -0500

Dear List - As a last-minute reminder, the Jan 31 deadline is fast approaching for the special issue of the IEEE Transactions on Speech and Audio Processing special issue we are editing on the topic of Statistical and Perceptual Audio Processing (following on from the workshop we held at ICSLP in Korea last year). Please see the attached announcement, and please do submit your work that considers auditory/perceptual processing problems by incorporating a statistical approach. It would be great to have as wide a range of perspectives represented as possible! If you have any questions about the special issue, feel free to contact me (or any of my co-editors). Thanks, and happy new year, DAn. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Call for Papers IEEE Transactions on Speech and Audio Processing Special Issue on Statistical and Perceptual Audio Processing Current trends in audio analysis are strongly founded in statistical principles, or on approaches that are influenced by empirically derived, or perceptually motivated rules of auditory perception. These approaches are orthogonal and new ideas that draw upon from both perceptual and statistical principles are likely to result in superior performance. However, how these two approaches relate to each other has not been thoroughly explored. In this special issue we invite researchers to submit papers on original and previously unpublished work on both approaches, and especially on hybrid techniques that combine perceptual and statistical principles, as applied to speech, music and audio analysis. Papers describing relevant research and new concepts are solicited on, but not limited to, the following topics: * Generalized audio analysis * Computational Auditory Scene Analysis (CASA) * Speech analysis * Perceptual aspects of statistical algorithms, * Music analysis such as independent component analysis and * Audio classification non-negative matrix factorization * Speech recognition * Hybrid methods that use CASA-like cues in a * Signal separation statistical framework, e.g. for separation * Multi-channel analysis or recognition. * Theoretical and empirical results on the unification of statistical and perceptually based approaches. SUBMISSION PROCEDURE Prospective authors should prepare manuscripts according to the Information for Authors as published in any recent issue of the Transactions and as available on the web at http://www.ieee.org/organizations/society/sp/infotsa.html. Note that all rules will apply with regard to submission lengths, mandatory overlength page charges, and color charges. Manuscripts should be submitted electronically through the online IEEE manuscript submission system at http://sps-ieee.manuscriptcentral.com/. When selecting a manuscript type, authors must click on Special Issue of T-SA on Statistical and Perceptual Audio Processing. Authors should follow the instructions for the IEEE Transactions on Speech and Audio Processing and indicate in the Comments to the Editor-in-Chief that the manuscript is submitted for publication in the Special Issue on Statistical and Perceptual Audio Processing. We require a completed copyright form to be signed and faxed to 1-732-562-8905 at the time of submission. Please indicate the manuscript number on the top of the page. SCHEDULE Submission deadline: 31 January 2005 Notification of acceptance: 30 July 2005 Final manuscript due: 1 September 2005 Tentative publication date: January 2006 GUEST EDITORS Dr. Bhiksha Raj Mitsubishi Electric Research Labs, Cambridge, MA. bhiksha(at)cs.cmu.edu Dr. Malcolm Slaney IBM, Almaden CA. malcolm(at)ieee.org Dr. Daniel Ellis Columbia University New York, NY. dpwe(at)ee.columbia.edu Dr. Paris Smaragdis Mitsubishi Electric Research Labs, Cambridge, MA. paris(at)merl.com Dr. Judith Brown Wellesley College, Visiting Scientist at MIT brown(at)media.mit.edu


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DAn Ellis <dpwe@ee.columbia.edu>
Electrical Engineering Dept., Columbia University