Reproduce “TopicVD: A Topic-Based Dataset of Video-Guided Multimodal Machine Translation for Documentaries” on OpenResearch
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About this paper
Jinze Lv, Jian Chen, Zi Long, Xianghua Fu, Yin Chen
A specialized dataset called TopicVD enables video-guided multimodal machine translation for documentaries through topic categorization and preservation of contextual information, while introducing a cross-modal bidirectional attention model that achieves minimum BLEU scores of 19.14 across diverse documentary domains.
Key insights
- Visual information consistently improves translation performance compared to text-only approaches
- Model performance depends heavily on domain matching between training and test data
- Global context from full documentary videos enhances translation accuracy
Summary by alphaXiv.
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