Chinese–Portuguese machine translation:a study on building parallel corpora from comparable texts
2018
Although there are increasing and significant ties between China and Portuguese-speaking countries, there is not much parallel corpora
in the Chinese–Portuguese language pair. Both languages are very populous, with 1.2 billion native Chinese speakers and 279 million
native Portuguese speakers, the language pair, however, could be considered as low-resource in terms of available parallel corpora. In
this paper, we describe our methods to curate Chinese–Portuguese parallel corpora and evaluate their quality. We extracted bilingual
data from Macao government websites and proposed a hierarchical strategy to build a large parallel corpus. Experiments are conducted
on existing and our corpora using both Phrased-Based Machine Translation (PBMT) and the state-of-the-art Neural Machine Translation
(NMT) models. The results of this work can be used as a benchmark for future Chinese–Portuguese MT systems. The approach we used
in this paper also show a good example on how to boost performance of MT systems for low-resource language pairs.
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