Three Strategies for Optimizing Caption Generation in Educational Videos
In response to the jargon-heavy and logical nature of educational videos, Tarsier can enhance the results in the following ways:
- Domain adaptation fine-tuning: LoRA fine-tuning of Tarsier2-Recap-7b using instructor-led video dataset (20-50 samples required)
- multimodal enhancement: PPT text is injected as prompt when PPT is synchronized with video input (format: [SLIDE: content text])
- Post-processing optimization: Work with OpenAI's Whisper for voice proofreading to correct spelling errors in technical terms
Practical tests show that the method improves terminology accuracy from 781 TP3T to 931 TP3T and formula description correctness by 351 TP3T in higher math videos.
This answer comes from the articleTarsier: an open source video comprehension model for generating high-quality video descriptionsThe
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