Impact of Combined Vocabulary Augmentation and Script Transliteration on POS Tagging in Low-Resource Languages

Abstract

Abstract: We present experiments with part-of-speech tagging for Bulgarian, a Slavic language with rich inflectional and derivational morphology. Unlike most previous work, which has used a small number of grammatical categories, we work with 680 morpho-syntactic tags. We combine a large morphological lexicon with prior linguistic knowledge and guided learning from a POS-annotated corpus, achieving accuracy of 97.98\%, which is a significant improvement over the state-of-the-art for Bulgarian.

Research Question

Does combining vocabulary augmentation with script transliteration improve Part-of-Speech tagging F1 scores on low-resource language benchmarks more than either method alone?

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