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LINGUIST List 22.2947

Tue Jul 19 2011

Calls: Computational Linguistics/China

Editor for this issue: Alison Zaharee <alisonlinguistlist.org>


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        1.     John Judge , META Workshop on Hybrid MT at MT Summit XIII

Message 1: META Workshop on Hybrid MT at MT Summit XIII
Date: 19-Jul-2011
From: John Judge <jjudgecomputing.dcu.ie>
Subject: META Workshop on Hybrid MT at MT Summit XIII
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Full Title: META Workshop on Hybrid MT at MT Summit XIII

Date: 19-Sep-2011 - 23-Sep-2011
Location: Xiamen, China
Contact Person: Christian Federmann
Meeting Email: < click here to access email >
Web Site: http://www.dfki.de/ml4hmt/

Linguistic Field(s): Computational Linguistics

Call Deadline: 27-Jul-2011

Meeting Description:

Workshop on Applying Machine Learning Techniques to Optimising the Division
of Labour in Hybrid MT
http://www.dfki.de/ml4hmt/
Conference: Machine Translation Summit XIII (MT Summit XIII)

The workshop will explore alternatives in order to provide optimal support
for Hybrid MT design, using sophisticated machine-learning techniques. One
further important objective of the workshop is to build bridges from MT to
the ML community to systematically and jointly explore the choice space for
Hybrid MT.

The workshop will open with an invited talk (speaker TBA), followed by two
technical paper sessions and a challenge or shared task session, and will
conclude with a discussion panel.

Call for Papers:

Topics of Interest of the Technical Papers:

Topics of interest include, but are not limited to:

- Use of Machine Learning techniques in combination / hybridization of
Machine Translation systems
- Using richer linguistic information in phrase-based SMT (e.g. in factored
models or hierarchical SMT)
- Using phrases from different types of MT in e.g. phrase-based SMT
- System combination approaches, either parallel in multi-engine MT (MEMT)
or sequential in statistical post-editing (SPMT)
- Learning resources (e.g. transfer rules, transduction grammars) for
probabilistic rule-based MT

All contributions will be published in the workshop proceedings.

Shared Task Description:

The 'Shared Task on Optimising the Division of Labour in Hybrid MT' is an
effort to trigger systematic investigation on improving state-of-the-art
Hybrid MT, using advanced machine-learning (ML) methodologies. Participants
are requested to build Hybrid/System Combination systems by combining the
output of several systems of different types, which is provided by the
organizers.

The main focus of the shared task is trying to answer the following question:

Could Hybrid/System Combination MT techniques benefit from extra
information (linguistically motivated, decoding and runtime) from the
different systems involved?

Data:

The participants are given a development bilingual set, aligned at a
sentence level. Each 'bilingual sentence' contains:

- the source sentence,
- the target (reference) sentence and
- the corresponding multiple output translations from 5 different systems,
based on different MT approaches (Apertium, Ramirez-Sanchez, 2006; Joshua,
Zhifei Li et al, 2009; Lucy, Alonso and Thurmair, 2003; Matrex, Penkale et.
al 2010) Metis, Vandeghinste et al., 2006). The output has been annotated
with system-internal information deriving from the translation process of
each of the systems (see below).

Baseline:

As a baseline we consider state-of-the-art open-source system-combination
systems, such as MANY (Barrault, 2010) and CMU-MEMT (Heafierld & Lavie, 2010).

Challenge:

Participants are challenged to build an MT mechanism that improves over the
baseline, by making effective use of the system-specific MT output. They
can either provide solutions based on an open source system, or develop
their own mechanisms. A suggested approach is given below.

- Spanish-English will be the language direction
- The development set can be used for tuning the systems during the
development phase. Final submissions have to include translation output on
a test set, which will be available one week before the submission deadline
- If you need language/reordering models they can be built upon the WMT
News Commentary (http://www.statmt.org/wmt11/)
- Participants can also make use of additional linguistic analysis tools,
if their systems require so, but they have to explicitly declare that upon
submission, so that they are judged as 'unconstrained' systems

Evaluation:

The system output will be judged via peer-based human evaluation. During
the evaluation phase, participants will be requested to rank system outputs
of other participants through a web-based interface (Appraise; Federmann
2010). Automatic metrics (BLEU, Papineni et. al, 2002) will be additionally
used.

System Description:

Shared task participants will be invited to submit short papers (4-6 pages)
describing their systems or their evaluation metrics (see instructions in
Submissions).

Important Dates:

May 20th - Release of data for the challenge
July 27th (extended deadline) - Paper Submissions due / Challenge results due
August 10th - Author notification / Release of challenge evaluation results
August 19th - Final version due

Submissions:

Technical papers and system description papers should follow the main
conference formatting requirements
(http://mt.xmu.edu.cn/mtsummit/SubmitPapers.html#). To submit
contributions, please follow the instructions at the Workshop management
system submission website:

https://www.easychair.org/account/signin.cgi?conf=ml4hmt

The contributions will undergo a double-blind review by members of the
programme committee. Please address queries to ml4hmteasychair.org.

Organization:

Chair: Toni Badia (Pompeu Fabra University, Spain)
Co-chairs: Christian Federmann (German Research Center for Artificial
Intelligence, Germany), Josef van Genabith (Dublin City University, Ireland)

Committee Members:

Maite Melero (Barcelona Media Innovation Center, Spain), Marta R.
Costa-jussa (Barcelona Media Innovation Center, Spain), Pavel Pecina
(Dublin City University, Ireland), Eleftherios Avramadis (German Research
Center for Artificial Intelligence, Germany)

Program Committee:

Eleftherios Avramidis (German Research Center for Artificial Intelligence,
Germany)
Rafael Banchs (Institute for Infocomm Reserarch - I2R, Singapore)
Loic Barrault (LIUM - University of Le Mans, France)
Chris Callison-Burch (Johns Hopkins University, MD, USA)
Jinhua Du (Faculty of Automation and Information Engineering, Xi'an
University of Technology, Xi'an, China)
Andreas Eisele (Directorate-General for Translation (DGT), Luxembourg)
Cristina Espana-Bonet (Technical University of Catalonia, TALP, Barcelona)
Patrick Lambert (LIUM - University of Le Mans, France)
Maite Melero (Barcelona Media Innovation Center, Spain)
Pavel Pecina (Dublin City University, Ireland)
Marta R. Costa-jussa (Barcelona Media Innovation Center, Spain)
David Vilar (German Research Center for Artificial Intelligence, Germany)




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