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

NAACL 2013 / SIGMT / SIGLEX Workshop Jun 13 or 14 2013, Atlanta, GA

*** Submission deadline: 01 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 01, 2013 Paper due date
Mar 29, 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/