AI subtitle generation optimization solution
CapCutAPI offers the following enhancements for the specific needs of educational video:
- pretreatment stage::
- utilization
pydubThe library is first processed for audio noise reduction - Separation of vocals and background music (requires installation of additional track processing tools)
- utilization
- parameter optimization::
- set up
language='zh-CN'when addingeducation=TrueParameter Optimization Terminology Recognition - Adjust the audio sampling rate to 16kHz to improve recognition stability.
- set up
- Multi-level calibration::
- First generate
.srtsubtitle file - Secondary calibration of timeline accuracy through the API
- Manual spot-checking of key passages before final exportation
- First generate
Measurement data shows that after optimization, the subtitle accuracy can be increased from 85% to 96%, and the generation time is shortened by 40%. For professional course videos, it is recommended to cooperate with ASR professional service API to further improve the effect.
This answer comes from the articleCapCutAPI: Open source tool for automated control of CapCut video clipsThe
May not be reproduced without permission:AI productivity tools " How to improve the efficiency and accuracy of educational video caption generation?
