Measuring bilingual corpus comparability

Abstract

Comparable corpora serve as an important substitute for parallel resources in cases of under-resourced language pairs. Previous work mostly aims to find a better strategy to exploit existing comparable corpora, while ignoring the variety in corpus quality. The quality of comparable corpora affects a lot its usability in practice, a fact that has been justified by several studies. However, researchers have not been able to establish a widely accepted and fully validated framework to measure corpus quality. We will thus investigate in this paper a comprehensive methodology to deal with the quality of comparable corpora. To be exact, we will propose several comparability measures and a quantitative strategy to test those measures. Our experiments show that the proposed comparability measure can capture gold-standard comparability levels very well and is robust to the bilingual dictionary used. Moreover, we will show in the task of bilingual lexicon extraction that the proposed measure correlates well with the performance of the real world application.

Towards Functionally Similar Corpus Resources for Translation

“…This research compared the results of clustering and topic modelling as ways to represent a corpus content using keywords statistics. In Li et al (2018), the authors compared the performance of several bilingual vocabulary overlap measures on a specifically designed corpus with known comparability levels and found that frequencies of words with a simple Presence/Absence weighting scheme outperformed other approaches.…”

“…One of the common approaches to corpus comparability is to define it as the domain similarity and to rely on the vocabulary overlap as the measure of comparability. A brief summary of possible interpretations of the concept and comparability measures can be found in Li et al (2018). The authors give a domain-based definition to crosslinguistically comparable corpora: "document sets in different languages that cover similar topics".…”