Building an English-Vietnamese Bilingual Corpus for Machine Translation

Abstract

Bilingual corpora are critical resources for machine translation research and development since parallel corpora contain translation equivalences of various granularities. Manual annotation of word alignments is of significance to provide a gold-standard for developing and evaluating both example-based machine translation models and statistical machine translation models. This paper presents research on building an English-Vietnamese parallel corpus, which is constructed for building a Vietnamese-English machine translation system. We describe the specification of collecting data for the corpus, linguistic tagging, bilingual annotation, and the tools specially developed for the manual annotation. An English-Vietnamese bilingual corpus of over 800,000 sentence pairs and 10,000,000 English words as well as Vietnamese words has been collected and aligned at the sentence level, and over 45,000 sentence pairs of this corpus have been aligned at the word level.