Bitext Mining

Bitext mining focuses on automatically extracting parallel sentence pairs from comparable corpora of different languages, a crucial task for building machine translation systems, especially for low-resource languages. Recent research emphasizes improving the accuracy and efficiency of bitext mining through advanced sentence embedding techniques, including contrastive learning and teacher-student training models that leverage multilingual and language-family-specific representations. These advancements are significantly improving the quality of mined parallel data, leading to better performance in downstream tasks like neural machine translation and ultimately expanding the availability of translation resources for a wider range of languages.