Appel: New Deadline for SSST-7 at NAACL 2013

[Thierry Hamon]

Date: Tue, 26 Feb 2013 03:27:53 -0800
From: "Carpuat, Marine" <Marine.Carpuat at cnrc-nrc.gc.ca>
Message-ID: <D7548FA9B5763F408F5EB57EE28383621AB12C2CA2 at NRCCENMB1.nrc.ca>
X-url: http://www.cs.ust.hk/~dekai/ssst/


SSST-7: Seventh Workshop on Syntax, Semantics and Structure in
Statistical Translation

NAACL 2013 / SIGMT / SIGLEX Workshop  Jun 13 2013, Atlanta, GA

*** NEW submission deadline: 15 Mar 2013 ***

The Seventh Workshop on Syntax, Semantics and Structure in Statistical
Translation (SSST-7) seeks to build on the foundations established in
the first six 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 two editions which had semantics for SMT as a special
theme. The issues of deep syntax and shallow semantics are closely
linked and SSST-7 continues to encourage submissions on semantics for MT
in a number of directions, including semantic role labeling and sense
disambiguation for translation and evaluation.

We invite papers on:

    * 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 S/TGs to related areas including:
        speech translation
        formal semantics and semantic parsing
        paraphrases and textual entailment
        information retrieval and extraction
    * syntactically- and semantically-motivated evaluation of MT

ORGANIZERS

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


IMPORTANT DATES

Mar 15, 2013    Paper due date
Apr   2, 2013    Notification of acceptance
Apr 12, 2013    Camera-ready deadline
Jun 13 or 14, 2013 Workshop

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

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