Bachelor/Master Theses - Machine Translation

The Lehrstuhl für Informatik 6 of the RWTH Aachen University is looking for Bachelor/Master students for research projects in the area of machine translation with statistical methods.

The following tasks are part of the thesis work:
  • implementation and testing of new approaches in machine translation;
  • the work consists of data preparation, implementation and testing of new algorithms;
  • the algorithms are to be applied to tasks with very large vocabularies, e.g. translation of speeches and debates of the European Parliament.
The candidates are expected:
  • to have good C/C++ programming skills
  • to have attended the lectures at the Lehrstuhl für Informatik 6 (Statistical Methods in Natural Language Processing, Pattern Recognition and Neural Networks) or to have gained knowledge of the respective content from other sources.

To apply, please contact:

Andreas Guta
Lehrstuhl für Informatik 6
Ahornstr. 55, RWTH Aachen
52056 Aachen

Room 6125b
Tel.: (0241) 80-21632
E-Mail: guta [-at-]


Finished and ongoing theses in this field include:

  • Felix Rietig:
    "Lexicalized Reordering Models for Phrase-based Statistical Machine Translation"
  • Julian Schamper:
    "Methods for Solving Substitution Ciphers"
  • Erik Scharwächter:
    "Discontinuous Phrases for Statistical Machine Translation"
  • Jan-Thorsten Peter:
    "Soft String-to-Dependency Hierarchical Machine Translation"
  • Christian Buck:
    "Conditional Random Fields for Statistical Machine Translation"
  • Markus Freitag:
    "Minimum Error Rate Training Extensions for Statistical Machine Translation"
  • Stephan Peitz:
    "Extending Statistical Machine Translation Using Syntax"
  • Jörn Wübker:
    "Training Phrase Models for Statistical Machine Translation"
  • Juri Ganitkevitch:
    "Lexical Triggers for Statistical Machine Translation"
  • Daniel Stein:
    "Morpho-Syntax Based Statistical Methods for Sign Language Translation"
  • Arne Mauser:
    "Improved Word Alignment and Phrase Extraction for Statistical Machine Translation"
  • Gregor Leusch:
    "String Distance Measures for Evaluation in Machine Translation"
  • Thomas Schoenemann:
    "Model-based Confidence Measures for Statistical Machine Translation"