Set-Theoretic Alignment for Comparable Corpora

Date: 07.08.2016


Abstract

We describe and evaluate a simple method to extract parallel sentences from comparable corpora. The approach, termed STACC , is based on expanded lexical sets and the Jaccard similarity coefficient. We evaluate our system against state-of-the-art methods on a large range of datasets in different domains, for ten language pairs, showing that it either matches or outperforms current methods across the board and gives significantly better results on the noisiest datasets. STACC is a portable method, requiring no particular adaptation for new domains or language pairs, thus enabling the efficient mining of parallel sentences in comparable corpora.

BIB_text

@Article {
title = {Set-Theoretic Alignment for Comparable Corpora},
pages = {2009-2018},
volume = {1},
keywds = {

Comparable Corpora, Alignment, Statistical machine Translation


}
abstract = {

We describe and evaluate a simple method to extract parallel sentences from comparable corpora. The approach, termed STACC , is based on expanded lexical sets and the Jaccard similarity coefficient. We evaluate our system against state-of-the-art methods on a large range of datasets in different domains, for ten language pairs, showing that it either matches or outperforms current methods across the board and gives significantly better results on the noisiest datasets. STACC is a portable method, requiring no particular adaptation for new domains or language pairs, thus enabling the efficient mining of parallel sentences in comparable corpora.


}
isbn = {978-1-945626-00-5},
doi = {10.18653/v1/P16-1189},
date = {2016-08-07},
year = {2016},
}
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