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LINGUIST List 17.3707

Thu Dec 14 2006

Calls: Semantics/USA; Comp Ling, Syntax, Translation/USA

Editor for this issue: Dan Parker <danlinguistlist.org>

As a matter of policy, LINGUIST discourages the use of abbreviations or acronyms in conference announcements unless they are explained in the text. To post to LINGUIST, use our convenient web form at http://linguistlist.org/LL/posttolinguist.html.
        1.    Yael Sharvit, Semantics And Linguistic Theory 17
        2.    David Chiang, Syntax and Structure in Statistical Translation

Message 1: Semantics And Linguistic Theory 17
Date: 11-Dec-2006
From: Yael Sharvit <salt17uconn.edu>
Subject: Semantics And Linguistic Theory 17

Full Title: Semantics And Linguistic Theory 17
Short Title: salt17

Date: 11-May-2007 - 13-May-2007
Location: Storrs, CT, USA
Contact Person: Yael Sharvit
Meeting Email: < click here to access email >
Web Site: http://salt17.uconn.edu

Linguistic Field(s): Semantics

Call Deadline: 02-Jan-2007

Meeting Description:

Natural language semantics and its relevance to linguistic theory.

Semantics and Linguistic Theory 17 will be held May 11-13, 2007 at the University of Connecticut in Storrs, CT. The invited speakers are:

Gennaro Chierchia, Harvard University
Veneeta Dayal, Rutgers University
Danny Fox, MIT
Thomas Ede Zimmerman, Johann Wolfgang Goethe-Universit├Ąt

We invite submissions of abstracts for 30-minute presentations (plus 10-minute discussions) on any topic pertaining to natural language semantics with relevance to linguistic theory. Abstracts must be anonymous and should be at most 2 pages (A4 or US Letter) in length (including examples and references) using a 12 pt font with 1-inch (2.5 cm) margins on all four sides. In the interest of fairness, these limitations will be strictly enforced.

Authors may be involved in at most two submissions and may be the sole author of at most one abstract. No single author will be allowed to give more than one presentation at the conference.

As a matter of general policy, SALT does not accept papers that at the time of the conference have been published or have been accepted for publication. In addition, preference will be given to presentations that are not duplicated at other major conferences. We therefore request that authors indicate prior or planned presentations of their papers along with their contact information when they submit their abstracts.

The deadline is January 2, 2007. We regret that we will not be able to consider abstracts arriving after this date. Speakers will be notified of the results of their abstract review by February 2007.

For instructions on abstract submission, please go to: http://salt17.uconn.edu

We look forward to seeing you here in Connecticut during SALT 17!!

Message 2: Syntax and Structure in Statistical Translation
Date: 11-Dec-2006
From: David Chiang <last-nameisi.edu>
Subject: Syntax and Structure in Statistical Translation

Full Title: Syntax and Structure in Statistical Translation
Short Title: SSST

Date: 26-Apr-2007 - 26-Apr-2007
Location: Rochester, NY, USA
Contact Person: David Chiang
Meeting Email: < click here to access email >
Web Site: http://www.cs.ust.hk/~dekai/ssst/

Linguistic Field(s): Computational Linguistics; Syntax; Translation

Call Deadline: 18-Jan-2007

Meeting Description:

Syntax and Structure in Statistical Translation (SSST)
NAACL-HLT Workshop
Rochester, New York, 26 April 2007

Tree-structured mappings between languages are widely recognized as
desirable for statistical machine translation, and there is mounting
interest in approaches built on a family of formalisms that includes
synchronous/transduction grammars and their tree transducer
equivalents. From this formal basis, there has been rapid progress on
many different fronts, ranging from purely mathematical results to
very strong showings in large-scale evaluations. The workshop on
Syntax and Structure in Statistical Translation seeks to bring
together researchers working on diverse aspects of
synchronous/transduction grammars in relation to statistical machine
translation, to build stronger connections in this area and stimulate
further progress.

For details and submission please see http://www.cs.ust.hk/~dekai/ssst/

Organizers: Dekai Wu (HKUST) and David Chiang (ISI)

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 a family of formalisms
that includes synchronous/transduction grammars (hereafter, 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.
There is active research ranging from formal properties of S/TGs to
large-scale end-to-end systems. There are approaches that make heavy
use of linguistic theory, and approaches that use little or none.
There is theoretical work characterizing the expressiveness and
complexity of particular formalisms, as well as empirical work
assessing their modeling accuracy and descriptive adequacy across
various language pairs. There is work being done to invent better
translation models, and work to design better algorithms. Recent years
have seen significant progress on all these fronts. In particular,
systems based on these formalisms are now top contenders in MT

In response to this bustling new situation, the workshop on Syntax and
Structure in Statistical Translation (SSST) seeks to bring together
researchers working on diverse aspects of S/TGs in relation to
statistical machine translation, to discuss current work, compare and
contrast different approaches, and identify the questions that are
most pressing for future progress in this area.

We invite papers on:

- syntax-based / tree-structured statistical translation 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 details and submission information please see http://www.cs.ust.hk/~dekai/ssst/


Dekai Wu (Hong Kong University of Science and Technology)
David Chiang (USC Information Sciences Institute)

Program Committee (partial):

Srinivas Bangalore (AT&T Research)
Daniel Gildea (University of Rochester)
Kevin Knight (USC Information Sciences Institute)
Daniel Marcu (USC Information Sciences Institute)
Hermann Ney (RWTH Aachen)
Owen Rambow (Columbia University)
Philip Resnik (University of Maryland)
Giorgio Satta (University of Padua)
Stuart Shieber (Harvard University)
Christoph Tillmann (IBM)
Enrique Vidal (Universidad Politecnica de Valencia)
Stephan Vogel (Carnegie Mellon University)
Taro Watanabe (NTT)
Andy Way (Dublin City University)
Richard Zens (RWTH Aachen)

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