Prefix-based IMT
Extension of Barrachina et al. implementation of the prefix-based interactive machine translation protocol. Taken a Moses search graph as an input, this software generates a word graph compatible with Barrachina et al. software and runs a user simulation. It was built in Python.

Segment-based IMT
Implementation of the segment-based interactive machine translation protocol from Segment-based Interactive-Predictive Machine Translation. It was built in Python profiting from Moses’ XML scheme.

Statistical dictionary
Given a parallel data set, this software trains an statistical dictionary for translating documents. It was built in Python and makes use of mgiza for computing IBM model 1 alignments.

Active learning
Implementation of the active learning protocol from A User Study of the Incremental Learning in NMT based on the toolkit OpenNMT-py. It was built in PyTorch.

Online demonstrator
Online demonstrator of several applications of machine translation for the processing of historical documents. The server is based on NMT-Keras.