Appel: SSST-6, Sixth Workshop on Syntax, Semantics and Structure in Statistical Translation (ACL 2012)

Tue Mar 13 20:50:19 UTC 2012

Date: Tue, 13 Mar 2012 15:46:19 -0400
From: Marine Carpuat <marine.carpuat at gmail.com>
Message-ID: <CAF6285kAVPkrPVYs_k8WUSH2pL88LnC9gNaRmBOZ-2ze+jH=Ag at mail.gmail.com>
X-url: http://www.cs.ust.hk/~dekai/ssst/

SSST-6: Sixth Workshop on Syntax, Semantics and Structure in Statistical
Translation
ACL 2012 / SIGMT / SIGLEX Workshop 12 July 2012, Jeju, Republic of Korea

*** New submission deadline: 15 Apr 2012 ***
*** Special theme: Semantic MT Evaluation ***

The Sixth Workshop on Syntax, Semantics and Structure in Statistical
Translation (SSST-6) seeks to build on the foundations established in
the first five SSST workshops, which brought together a large number of
researchers working on diverse aspects of structure, semantics and
representation in relation to statistical machine translation. Its
program each year has comprised high-quality papers discussing current
work spanning topics including: new grammatical models of translation;
new learning methods for syntax- and semantics-based models; formal
properties of synchronous/transduction grammars (hereafter S/TGs);
discriminative training of models incorporating linguistic features;
using S/TGs for semantics and generation; and syntax- and
semantics-based evaluation of machine translation.

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 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 evaluations.

At the same time, SMT has seen a movement toward semantics over the past
few years, which has been reflected at recent SSST workshops, including
the last edition which had semantics for SMT as a special theme.  The
issues of deep syntax and shallow semantics are closely linked and
SSST-6 encourages submissions on semantics for MT in a number of
directions, including semantic role labeling (SRL) for SMT, WSD for SMT
and in particular, semantics for MT evaluation.  In order to emphasize
the need to evaluate MT in a way that properly assesses preservation of
structure and semantics, SSST-6 is highlighting Semantic MT Evaluation
as a special workshop theme.

We invite papers on:

* syntactically- and semantically-motivated evaluation of MT
* syntax-based / semantics-based / tree-structured SMT
* machine learning techniques for inducing structured translation models
* algorithms for training, decoding, and scoring with semantic
  representation structure
* empirical studies on adequacy and efficiency of formalisms
* creation and usefulness of syntactic/semantic resources for MT
* formal properties of synchronous/transduction grammars
* learning semantic information from monolingual, parallel or comparable
  corpora
* unsupervised and semi-supervised word sense induction and
  disambiguation methods for MT
* lexical substitution, word sense induction and
  disambiguation,semantic role labeling, textual entailment, paraphrase
  and other semantic tasks for MT
* semantic features for MT models (word alignment, translation
  lexicons, language models, etc.)
* evaluation of syntactic/semantic components within MT (task-based
  evaluation)
* scalability of structured translation methods to small or large data
* applications of synchronous/transduction grammars to areas including:
  speech translation, formal semantics and semantic parsing, paraphrases
  and textual entailment, information retrieval and extraction, etc.

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

SPECIAL THEME: SEMANTIC MT  EVALUATION

Ongoing work suggests that MT evaluation is improved by generalizing
across similar word meanings (Zhou et al., 2006; Apidianaki et al, 2009;
Snover et al., 2009; Denkowski and Lavie, 2010), and explicitly modeling
preservation of meaning with textual entailment (Padó et al.  2009), or
semantic frames (Lo and Wu, 2011).  However, crucial questions such as
what frameworks are best suited to measure MT quality in general, and
the impact of semantic modeling in MT evaluation remain unanswered. With
this year's special theme, we seek to bring together researchers working
on semantics and on translation evaluation in order to encourage
cross-pollination of ideas, share insights into the needs of MT
evaluation and what current developments in semantics have to offer. We
particularly encourage the submission of papers addressing the following
issues related to semantics-driven evaluation of MT:

 * MT evaluation  metrics generalizing across similar word meanings
 * MT evaluation metrics explicitly modeling preservation of meaning via
   textual entailment, semantic frames, etc
 * New frameworks to measure MT quality using semantic information,
   including machine learning approaches
 * Evaluation of the impact of semantic modeling on MT evaluation
 * Use of semantic information for quality/confidence estimation (MT
   evaluation without reference translations)

ORGANIZERS

Marine CARPUAT, National Research Council Canada
Lucia SPECIA, University of Sheffield
Dekai WU, Hong Kong University of Science & Technology

IMPORTANT DATES

Submission deadline:  15 Apr 2012
Notification to authors:  4 May 2012
Camera copy deadline:  11 Apr 2012

SUBMISSION

Papers will be accepted on or before 2 Apr 2012 in PDF or Postscript
formats via the START system:
https://www.softconf.com/acl2012/ssst-6/. Submissions should follow
the ACL 2012 length and formatting requirements for long papers of
eight (8) pages of content with two (2) additional pages of
references, found at http://www.acl2012.org/call/sub01.asp

CONTACT

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

PROGRAM COMMITTEE

Marianna Apidianaki, LIMSI-CNRS
Wilker Aziz, University of Wolverhampton
Srinivas Bangalore, AT&T Research
David Chiang, USC ISI
Colin Cherry, National Research Council Canada
Mona Diab, Columbia University
Alexander Fraser, University of Stuttgart
Daniel Gildea, University of Rochester
Nizar Habash, Columbia University
Yifan He, Dublin City University
Philipp Koehn, University of Edinburgh
Kevin Knight, USC ISI
Alon Lavie, CMU
Yanjun Ma, Baidu
Daniel Marcu, USC ISI and Language Weaver
Lluìs Màrquez, Universitat Politècnica de Catalunya
Sudip Kumar Naskar, Dublin City University
Hwee-Tou Ng, National University of Singapore
Daniele Pighin, Universitat Politècnica de Catalunya
Markus Saers, HKUST
Libin Shen, IBM Research
Matthew Snover, BBN
John Tinsley, Dublin City University
Stephan Vogel, Qatar Computing Research Institute
Taro Watanabe, NICT
Deyi Xiong, National University of Singapore
François Yvon, Université Paris Sud 11

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