Bilingual cue word optimization methodology
For Step-Video-T2V's bilingual support feature, attention should be paid to achieve the best video generation results:
- verbal mixing strategy: A mix of English and Chinese cues for richer features (e.g. "a cat playing in the park").
- Cultural contextualization: Chinese tips need to include quantifiers ("an airplane" rather than "an aircraft"), and English tips should avoid ambiguous prepositions.
- Structured prompt templates: Suggested four-part structure of [subject] + [action] + [setting] + [style]
Hands-on advice:
- Bi-directional checking of semantic consistency using specialized translation tools
- Adding visual suffixes to abstract concepts (e.g., "futuristic city, cyberpunk style, neon light")
- Batch testing of different language combinations via `.txt` files
Typical optimization cases:
Basic Tip: "Puppy Running"
Optimized: "A golden retriever golden retriever running happily on a sunny lawn, 4K HD, slow motion"
The bilingual_prompts.csv provided with the project contains validated templates for efficient prompts.
This answer comes from the articleStep-Video-T2V: A Vincennes Video Model Supporting Multilingual Input and Long Video GenerationThe
May not be reproduced without permission:AI productivity tools " How to optimize Step-Video-T2V's bilingual cue words for best video quality?
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