Signal Processing and Speech Communication Laboratory
hometheses & projects › Machine Translation with Recurrent Neural Networks

Machine Translation with Recurrent Neural Networks

Master Thesis
Announcement date
06 Oct 2015
Research Areas

Short Description

neural translation models

Your Tasks 

  • Redroduce and compare to state-of-the-art neural translation models
  • Extend existing models in Python and Theano (libary for GPU computing)
  • Analyze the implemented systems in terms of accuracy and computational performance

Your Profile 

  • Very good theoretical and mathmatical background (mandatory) 
  • Good knowledge in machine learning
  • Very good knowledge and experience in Python programming (mandatory)

Additional Information

As this work combines theoretical and experimental aspects of non-standard methods, a very good mathmatical and programming background is mandatory. This thesis project is planned for a duration of 6 months starting immediately. It has a good chance for publications.


Martin Ratajczak ( or +43 (316) 873 - 4379)


[1] D. Bahdanau, K. Cho, andY. Bengio. Neuralmachine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473, 2014

[2] I. Sutskever, O. Vinyals, Q. V. Le. Sequence to Sequence Learning with Neural Networks, 2014