Feature-rich unsupervised word alignment models
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README.md

This project is about feature-rich unsupervised word alignment models. At this point we are working on 0th order HMMs, that is, IBM2-like models. We follow Berg-Kirkpatrick et al (2010) and reparameterise IBM2's categorical distributions using exponentiated linear functions (a log-linear parameterisation).

This code-base started as Guido Linder's final project towards his BSc.

Build

Check our build instructions.

Usage

For a help message try:

$ python -m lola.aligner --help

Check some examples.

You can train different models with lola, check our configuration file format.