Hybrid Machine Translation focuses on combining the best properties of
different Machine Translation (MT) paradigms. Nowadays, it is very popular
to include linguistic features in Statistical Machine Translation (SMT)
systems or to modify the standard Rule-based Machine Translation (RBMT)
architecture to include statistical knowledge. Other ways of hybridization
include the system combination techniques which may combine a rich variety
of translation paradigms.

This special issue in the prestigious Computer Speech and Language journal
will cover different approaches from Hybrid Machine Translation and take
advantage of the latest and leading research to discuss the progress in the
field.

This special issue invites contributions related to (but not limited):

1. theoretical and experimental design of hybrid MT architectures

2. experimental results with hybrid MT systems guided by corpus-based or
rule-based systems

3. introduction of linguistics in corpus-based approaches

4. rule-based systems extended or built with statistical information

5. induction of lexical or grammatical transfer rules from corpora

6. description of open source tools and language resources for hybrid MT

7. description of computationally efficient algorithms for hybrid MT

8. applications of hybrid MT systems

9. hybrid methods applied to spoken language translation (SLT)

10. hybrid evaluation methods

11. system combination of different MT and SLT paradigms.


Submission procedure
-----------------------------------------
Prospective authors should follow the regular guidelines of the Computer
Speech and Language Journal for electronic submission
(http://ees.elsevier.com/csl). During submission authors must select "SI:
Hybrid Machine Translation" as Article Type.


Important dates
-------------------------------
1st March 2014: Deadline for Submissions
1st June 2014: Notification of Resubmission
1st July 2014: Deadline for Resubmission
1st August 2014: Final Decision


Guest Editors
---------------------------
Dr. Marta R. Costa-juss�, Institute for Infocomm Research, Singapore,
martaruizcostajussa@gmail.com
Prof. Jos� A. R. Fonollosa, Universitat Polit�cnica de Catalunya,
Barcelona, jose.fonollosa@upc.edu