Indonesia's linguistic landscape is remarkably diverse, encompassing over 700 languages and dialects, making it one of the world's most linguistically rich nations. This diversity, coupled with the widespread practice of code-switching and the presence of low-resource regional languages, presents unique challenges for modern pre-trained language models. In response to these challenges, we developed NusaBERT, building upon IndoBERT by incorporating vocabulary expansion and leveraging a diverse multilingual corpus that includes regional languages and dialects. Through rigorous evaluation across a range of benchmarks, NusaBERT demonstrates state-of-the-art performance in tasks involving multiple languages of Indonesia, paving the way for future natural language understanding research for under-represented languages.
NusaBERT: Teaching IndoBERT to be Multilingual and Multicultural
NusaBERT, an enhanced version of IndoBERT, achieves superior performance on multilingual tasks involving Indonesian languages by expanding vocabulary and utilizing a diverse corpus.
- Year
- 2024
- Venue
- arXiv 2024
- Authors
- 4
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- Abstract onlyARXIV-DEFAULT
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- arxiv.org/abs/2403.01817ARXIV-DEFAULT
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