The "Second Workshop on Applying Machine Learning Techniques to Optimise the Division of Labour in Hybrid MT (ML4HMT-12)” is an effort to trigger a systematic investigation on improving state-of-the-art hybrid machine translation, making use of advanced machine-learning (ML) methodologies.
It follows the ML4HMT-11 workshop, which took place in November 2011 in Barcelona. The first workshop also road-tested a shared task (and associated data set) and laid the basis for a broader reach in 2012.
ML4HMT-12 involves regular papers on hybrid MT as well as a Shared Task. More information is available in the call for papers.
We are soliciting original papers on hybrid MT, including (but not limited to):
Full papers should be anonymous and follow the COLING full paper format.
Participants are invited to build hybrid machine translation systems and/or system combinations by using the output of several MT systems of different types, as provided by the organisers (updated ML4HMT corpus).
The precursor workshop ML4HMT-11 was held on November 19th, 2011 in Barcelona, Spain. The original call for papers is available here, the workshop program—including papers and presentations—can be found here.
An overview on T4ME WP2 »Optimising the Division of Labour in Hybrid MT«, funded by DG INFSO through the Seventh Framework Programme, grant agreement no.: 249119, is available here.