Aligning words using matrix factorisation
Cyril Goutte, Kenji Yamada, Eric Gaussier
Aligning words from sentences which are mutual translations is an important problem in different settings,
such as bilingual terminology extraction, Machine Translation, or projection of linguistic features.
Here, we view word alignment as matrix factorisation. In order to produce proper alignments, we show that
factors must satisfy a number of constraints such as orthogonality. We then propose an algorithm for
orthogonal non-negative matrix factorisation, based on a probabilistic model of the alignment data, and apply it
to word alignment. This is illustrated on a French-English alignment task from the Hansard.
42nd Annual Meeting of the Association for Computational Linguistics, Barcelona, Spain, July 25-26, 2004.
2004_015.pdf (88.09 kB)