Second Workshop on

Applying Machine Learning Techniques

to Optimise the Division of Labour

 in Hybrid MT (ML4HMT)



December 2012




Vassilina Nikoulina, Agnes Sandor, and Marc Dymetman:

 Hybrid adaptation of named entity recognition for statistical machine translation. pp.1-15.


Li Maoxi and Wang Mingwen:

Confusion network based system combination for Chinese translation output: word-level or character-level. pp.17-24.


Kartik Asooja, Jorge Gracia, Nitish Aggarwal, and Asunión Gómez Pérez:

Using cross-lingual explicit semantic analysis for improving ontology translation. pp.25-35.


Xiaofeng Wu, Tsyoshi Okita, Josef van Genabith, and Qun Liu:

System combination with extra alignment information. pp.37-44.


Tsuyoshi Okita, Antonio Toral, and Josef van Genabith:

Topic modeling-based domain adaptation for system combination. pp.45-53.


Tsuyoshi Okita, Raphaël Rubino, and Josef van Genabith:

Sentence-level quality estimation for MT system combination. pp.55-63.


Tsuyoshi Okita:

Neural probabilistic language model for system combination. pp.65-75.


Christian Federmann:

System combination using joint, binarised feature vectors. pp.77-83.


Christian Federmann, Tsuyoshi Okita, Maite Melero, Marta R.Costa-jussà, Toni Badia, and Josef van Genabith:

Results from the ML4HMT-12 shared task on applying machine learning techniques to optimise the division of labour in hybrid machine translation.