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Category:   E-CFP
Subject:   "New Approaches to Statistical Speech and Text Processing" (special issue of IEEE Trans ASLP)
From:   Steve Renals
Email:   s.renals_(on)_ed.ac.uk
Date received:   06 Nov 2006
Deadline:   15 Jun 2006

Call for Papers Special Issue of the IEEE Transactions on Audio, Speech and Language Processing on New Approaches to Statistical Speech and Text Processing Dramatic advances in automatic speech recognition (ASR) technology in recent years has enabled serious growth in spoken language processing research, both for human-computer interaction and spoken document processing. The challenges of working with spoken language, including ASR errors and disfluencies, were major factors in the adoption of statistical techniques in the language processing community. Statistical methods now dominate many areas of text processing as well, enabled by growing collections of linguistic data resources and developments in machine learning. While transfer of methods from spoken- to written- language processing continues, advances in written-language processing also now have a significant impact on spoken-language processing. This issue seeks to highlight the cross-fertilization in speech and text processing by publishing novel statistical modeling and learning methods that span a variety of language processing applications. We invite papers describing new approaches to statistical language processing of both spoken and written language. Submissions must not have been previously published, with the exception that substantial extensions of conference papers will be considered. Of particular interest are methods that transfer recent developments from text processing to speech processing and vice versa, but new methods in one domain are also welcome. Papers describing new strategies for integrating acoustic and linguistic cues in spoken language processing are also encouraged. Topics of interest include: - Unsupervised and semi-supervised learning - Discriminative learning - Transfer or adaptation to new domains - Active learning - Reinforcement learning - Memory-based learning and neighborhood methods - Novel statistical models - Statistical methods for feature selection or transformation Specific applications of interest include information extraction, question answering, text segmentation and classification, summarization, translation, language generation and spoken language dialogs. Papers that address component problems of these larger applications are also encouraged, including parsing, discourse analysis, and talker interaction analysis. The issue aims to cover a variety of applications as well as different statistical methods. 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 TASLP on New Approaches to Statistical Speech and Text Processing". Authors should follow the instructions for the IEEE Transactions Audio, Speech and Language Processing and indicate in the Comments to the Editor-in-Chief that the manuscript is submitted for publication in the Special Issue on New Approaches to Statistical Speech and Text 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: 15 June 2007 Notification of final acceptance: 15 December 2008 Final manuscript due: 1 February 2008 Publication date: May 2008 Guest Editors: Dr. Bill Byrne Cambridge University, UK wjb31_(on)_cam.ac.uk Dr. Mark Johnson Brown University, USA Mark_Johnson_(on)_brown.edu Dr. Lillian Lee Cornell University, USA llee_(on)_cs.cornell.edu Dr. Steve Renals University of Edinburgh, UK s.renals_(on)_ed.ac.uk _______________________________________________ Elsnet-list mailing list Elsnet-list_(on)_elsnet.org http://mailman.elsnet.org/mailman/listinfo/elsnet-list

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