Utilize Transformers for translating Wikipedia category names
This provides an incremental solution for Wikipedia editors and users in Vietnamese to automate category translation with limited computational resources.
The paper tackled the problem of manually creating Wikipedia categories by building language models to translate English category names to Vietnamese, achieving a BLEU score of 0.73 with the OPUS-MT-en-vi model.
On Wikipedia, articles are categorized to aid readers in navigating content efficiently. The manual creation of new categories can be laborious and time-intensive. To tackle this issue, we built language models to translate Wikipedia categories from English to Vietnamese with a dataset containing 15,000 English-Vietnamese category pairs. Subsequently, small to medium-scale Transformer pre-trained models with a sequence-to-sequence architecture were fine-tuned for category translation. The experiments revealed that OPUS-MT-en-vi surpassed other models, attaining the highest performance with a BLEU score of 0.73, despite its smaller model storage. We expect our paper to be an alternative solution for translation tasks with limited computer resources.