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

Machine Translation with Recurrent Neural Networks

Status
Open
Type
Master Thesis
Announcement date
06 Oct 2015
Mentors
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.

Contact

Martin Ratajczak (martin.ratajczak@tugraz.at or +43 (316) 873 - 4379)

References

[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