Educational video caption generation requires special attention to terminological accuracy and speaker correspondence:
Customized Solutions
- Subject dictionary import: Add terminology dictionaries (e.g. medical_terms.txt) to the config directory to improve the recognition rate.
- Speaker registration system: Pre-recorded voice samples for fixed teachers, named and saved as teacher_voice.wav
- speech rate adaptation: Settings
max_sentence_lengthParameters adjust the length of the break (8-12 seconds recommended)
Specific implementation steps
- utilization
ffmpeg -i lecture.mp4 -vn lecture.wavExtract pure audio - Set in config.yaml:
speaker_profiles: [teacher,student1,student2]dictionary_path: config/edu_terms.txt - After running the main program, replace terms in bulk with regular expressions (e.g., replace "DNA" with "DNA" uniformly).
Teaching Scene Specialization Techniques
1. Introduction of question-and-answer sessionsspeaker_transition_threshold=0.3Improved switching sensitivity
2. Add[黑板板书]Scene labeling such as
3. Preserve timestamp alignment when outputting bilingual subtitles
This answer comes from the articleSimple Subtitling: an open source tool for automatically generating video subtitles and speaker identificationThe
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