EU-BRIDGE’s open source

Important technology developments over the course of the project are available as open source toolkits.

The RWTH open source neural network toolkit for speech recognition

Intensified use of neural networks in the models of speech translation systems, are available here as open source toolkit. Experimental evaluation confirmed the competitive recognition accuracy, while 
requiring far less computational time than other tools. It supports CPU multi-threading and general purpose computing on GPUs.

Free usage including redistribution and modification for non-commercial use under http://www.hltpr.rwth-aachen.de/rasr

Jane - The RWTH Aachen University Statistical Machine Translation Toolkit

Jane is RWTH's open source statistical machine translation toolkit. Jane supports state-of-the-art techniques for phrase-based and hierarchical phrase-based machine translation. Many advanced features are implemented in the toolkit, as for instance forced alignment phrase training for the phrase-based model and several syntactic extensions for the hierarchical model. https://www-i6.informatik.rwth-aachen.de/jane

Kaldi open source toolkit

Kaldi is a toolkit for speech recognition written in C++ and licensed under the Apache License v2.0. Kaldi is intended for use by speech recognition researchers. http://kaldi.sourceforge.net

Moses statistical machine translation system

Moses is a statistical machine translation system that allows you to automatically train translation models for any language pair. All you need is a collection of translated texts (parallel corpus). Once you have a trained model, an efficient search algorithm quickly finds the highest probability translation among the exponential number of choices. http://www.statmt.org/moses/ and the github directory: https://github.com/moses-smt/mosesdecoder .

The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no 287658