cdec

Features

cdec is a decoder, aligner, and learning framework for statistical machine translation and similar structured prediction models.

• Translation and alignment modeling based on finite-state transducers and synchronous context-free grammars.
• Implementations of several parameter learning algorithms.
• Fast, extensible C++ implementation and Python interface (pycdec).
• Modular architecture that separates search space construction, rescoring, and inference.

Documentation

• Try this step-by-step tutorial to start building a system!
• The User guide contains an introduction to cdec's features.
• The Documentation contains more information for users already familiar with cdec.
• Concepts provides an basic overview of statistical machine translation concepts.
• Developers should have a look at this section for documentation about the code.

Downloads

cdec is developed on Github, and interested developers are encouraged to fork us, develop the project further, and submit patches.

Citation

If you make use of cdec, please cite:

C. Dyer, A. Lopez, J. Ganitkevitch, J. Weese, F. Ture, P. Blunsom, H. Setiawan, V. Eidelman, and P. Resnik. cdec: A Decoder, Alignment, and Learning Framework for Finite-State and Context-Free Translation Models. In Proceedings of ACL, July, 2010. [bibtex]

License

The cdec source code is released under the terms of the Apache License, Version 2.0. The libLBFGS library source code is distributed with cdec, and it is released under the terms of the MIT License.

Acknowledgements

cdec was developed and is supported in part by grants from DARPA, the National Science Foundation, and the US Army Research Office.