[Corpora-List] CFP: ACL Workshop on Syntax and Structure in Statistical Translation

[David Chiang]

                              ACL-08:HLT
                          Second Workshop on
         SYNTAX AND STRUCTURE IN STATISTICAL TRANSLATION (SSST-2)

                       June 2008, Columbus, Ohio
                  
The Second Workshop on Syntax and Structure in Statistical Translation
(SSST-2) seeks to build on the foundations established in the first
SSST which was held as an AMTA-sponsored workshop at NAACL-HLT
2007. SSST-1 brought together a large number of researchers working on
diverse aspects of synchronous/transduction grammars (hereafter,
S/TGs) in relation to statistical machine translation. Its program
comprised high-quality papers discussing current work spanning topics
including: new grammatical models of translation; discriminative
training of syntax-based models; using S/TGs for semantics and
generation; syntax-based evaluation of machine translation; and formal
properties of S/TGs.

The need for structural mappings between languages is widely
recognized in the fields of statistical machine translation and spoken
language translation, and there is a growing consensus that these
mappings are appropriately represented using S/TGs and their
tree-transducer equivalents. To date, flat-structured models, such as
the word-based IBM models of the early 1990s or the more recent
phrase-based models, remain widely used. But tree-structured mappings
arguably offer a much greater potential for learning valid
generalizations about relationships between languages. Within this
area of research there is a rich diversity of approaches, and recent
years have seen significant progress on many fronts.

SSST-2 seeks to bring together researchers in these diverse areas,
providing a forum for discussing recent results, comparing and
contrasting different approaches, and identifying the questions that
are most pressing for future progress in this field. We invite papers
on:

  * syntax-based / tree-structured statistical translation models
    and language models
  * machine learning techniques for inducing structured translation
    models
  * algorithms for training, decoding, and scoring with S/TGs
  * empirical studies on adequacy and efficiency of formalisms
  * studies on the usefulness of syntactic resources for translation
  * formal properties of S/TGs
  * scalability of structured translation methods to small or large data
  * applications of S/TGs to related areas including:
    * speech translation
    * formal semantics and semantic parsing
    * paraphrases and textual entailment
    * information retrieval and extraction

For more information: http://www.cs.ust.hk/~dekai/ssst/

SUBMISSION

Papers will be accepted on or before 17 Mar 2008 in PDF or Postscript
formats via the START system at
https://www.softconf.com/acl08/ACL08-WS03/. Submissions should follow
the ACL-08: HLT formatting requirements, found at
http://www.ling.ohio-state.edu/acl08/stylefiles.html.

IMPORTANT DATES

Submission deadline: 17 Mar 2008
Notification to authors: 7 Apr 2008
Camera-ready copy deadline: 21 Apr 2008

ORGANIZERS

Dekai WU (Hong Kong University of Science and Technology)
David CHIANG (USC Information Sciences Institute)

PROGRAM COMMITTEE

Srinivas BANGALORE (AT&T Research)
Marine CARPUAT (Hong Kong University of Science and Technology)
Pascale FUNG (Hong Kong University of Science and Technology)
Daniel GILDEA (University of Rochester)
Kevin KNIGHT (USC Information Sciences Institute)
Jonas KUHN (Potsdam)
Yang LIU (ICT)
Daniel MARCU (USC Information Sciences Institute)
Yuji MATSUMOTO (Nara Institute of Science and Technology)
Hermann NEY (RWTH Aachen)
Owen RAMBOW (Columbia University)
Philip RESNIK (University of Maryland)
Stefan RIEZLER (Google)
Libin SHEN (BBN)
Christoph TILLMANN (IBM)
Stephan VOGEL (Carnegie Mellon University)
Taro WATANABE (NTT)
Andy WAY (Dublin City University)
Yuk-Wah WONG (Google)
Richard ZENS (Google)

CONTACT
Please send inquiries to ssst at cs.ust.hk.

Last updated: 2008.02.01



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