[Corpora-List] CFP for "New approaches to statistical speech and text processing": IEEE TASLP special issue -- Deadline extension

[Bill Byrne]

** Submission deadline extended to 29 June 2007 **

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:	29 June 2007
Notification of final acceptance:	15 December 2007
Final manuscript due: 	1 February 2008
Publication date:	May 2008


Guest Editors:

Dr. Bill Byrne	  Cambridge University, UK	   wjb31_AT_cam.ac.uk
Dr. Mark Johnson  Brown University, USA	       Mark_Johnson_AT_brown.edu
Dr. Lillian Lee   Cornell University, USA	   llee_AT_cs.cornell.edu
Dr. Steve Renals  University of Edinburgh, UK  s.renals_AT_ed.ac.uk

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